Optimize Deep Learning Projects on Upwork

We would like to build a service that will run once an hour, connect to our database based in MSSQL read some client details and send it to ChatGPT API and return data based on that data.
Once the data is returned the service will write this info back into the database in a dedicated table.
More details will be provided for candidates that are suitable

Skills: Python, Deep Learning, SQL, OpenAI API, ChatGPT API

We are seeking an AI expert to provide guidance on training machine learning models and setting up the necessary environments. The ideal candidate will also offer advice on implementing AI features effectively in our projects. Your expertise will play a critical role in enhancing our AI capabilities and ensuring successful deployment. If you have a strong background in AI and a passion for sharing knowledge, we would love to hear from you!

Skills: Python, Machine Learning, Artificial Intelligence, Deep Learning, TensorFlow

We are looking for a highly skilled AI/ML Engineer to develop, train, and deploy intelligent machine learning models for price optimization and predictive analytics. The role involves working with real-time data, forecasting models, and competitive pricing strategies.

? Key Responsibilities:

✅ Develop and implement AI-based predictive models using historical data.
✅ Train ML models to analyze price fluctuations, demand patterns, and external data sources.
✅ Design & optimize dynamic bidding algorithms for real-time pricing.
✅ Integrate AI models with external APIs for real-time data analysis.
✅ Develop AI-driven secondary market pricing optimization.
✅ Implement Reinforcement Learning for smart pricing strategies.
✅ Build AI models for competitor price tracking and trend analysis.
✅ Deploy AI models in a scalable cloud-based architecture.
✅ Work closely with backend developers to integrate AI-based recommendations.

? Required Technical Skills:

✅ Machine Learning & Deep Learning: Experience with TensorFlow, PyTorch, Scikit-Learn, Keras.
✅ Predictive Analytics & Time-Series Forecasting: Using XGBoost, LSTMs, Random Forest, Bayesian Models.
✅ Big Data Processing: Experience with Apache Spark, Hadoop, Pandas, NumPy for large-scale datasets.
✅ NLP & Data Scraping: Building AI models to track external sources and analyze trends.
✅ Reinforcement Learning (RL): Implementing AI-driven dynamic pricing strategies.
✅ Cloud Deployment & Scalability: AWS Lambda, Google Cloud AI, Azure ML for hosting AI services.
✅ Database & Data Engineering: PostgreSQL, MongoDB, Redis for real-time data storage.
✅ API Development & Integration: Working with RESTful APIs, GraphQL.
✅ Smart Contract & Web3 Integration: Knowledge of blockchain automation and AI-driven Web3 transactions (Preferred).

Skills: Machine Learning (ML), Data Scraping, Tensorflow, Predictive Analytics, NLP

We are looking for a highly skilled AI/ML Engineer to develop, train, and deploy intelligent machine learning models for price optimization and predictive analytics. The role involves working with real-time data, forecasting models, and competitive pricing strategies.

? Key Responsibilities:

✅ Develop and implement AI-based predictive models using historical data.
✅ Train ML models to analyze price fluctuations, demand patterns, and external data sources.
✅ Design & optimize dynamic bidding algorithms for real-time pricing.
✅ Integrate AI models with external APIs for real-time data analysis.
✅ Develop AI-driven secondary market pricing optimization.
✅ Implement Reinforcement Learning for smart pricing strategies.
✅ Build AI models for competitor price tracking and trend analysis.
✅ Deploy AI models in a scalable cloud-based architecture.
✅ Work closely with backend developers to integrate AI-based recommendations.

? Required Technical Skills:

✅ Machine Learning & Deep Learning: Experience with TensorFlow, PyTorch, Scikit-Learn, Keras.
✅ Predictive Analytics & Time-Series Forecasting: Using XGBoost, LSTMs, Random Forest, Bayesian Models.
✅ Big Data Processing: Experience with Apache Spark, Hadoop, Pandas, NumPy for large-scale datasets.
✅ NLP & Data Scraping: Building AI models to track external sources and analyze trends.
✅ Reinforcement Learning (RL): Implementing AI-driven dynamic pricing strategies.
✅ Cloud Deployment & Scalability: AWS Lambda, Google Cloud AI, Azure ML for hosting AI services.
✅ Database & Data Engineering: PostgreSQL, MongoDB, Redis for real-time data storage.
✅ API Development & Integration: Working with RESTful APIs, GraphQL.
✅ Smart Contract & Web3 Integration: Knowledge of blockchain automation and AI-driven Web3 transactions (Preferred).

Skills: Machine Learning (ML), Data Scraping, Tensorflow, Predictive Analytics, NLP

We are seeking a skilled Generative AI Music Model Engineer to join our innovative team. The ideal candidate will develop and optimize models that generate original music compositions. You will work with state-of-the-art AI technologies and collaborate with musicians to create unique soundtracks. Proficiency in machine learning frameworks and a passion for music is essential. If you have a strong background in AI and music technology, we’d love to hear from you!

Skills: Python, Machine Learning, Deep Learning, Music, Audio & Music Software, Artificial Intelligence, Generative AI, Generative AI Prompt Engineering, Generative AI Software

📌 Overview
We are developing an innovative wearable technology that leverages AI-driven real-time data recognition to enhance human interaction and user experience. The project involves building a cutting-edge AI model that processes biometric, motion, and voice data to provide intelligent and adaptive feedback with high accuracy.

We are seeking a world-class AI Engineer with expertise in multimodal AI, on-device & cloud AI optimization, and real-time data classification models to develop, test, and refine the system. The role requires close collaboration with our firmware, UX/UI, and data science teams to ensure seamless real-time processing while maintaining efficiency and accuracy.

📌 Scope of Work

✅ Develop & Optimize AI-Based Wearable Data Recognition Model

Build real-time AI models to classify sensor data patterns from multiple sources (HR, SpO2, movement, voice, etc.).
Design low-latency AI optimized for wearable integration.
Train models on real-world datasets to ensure high accuracy across diverse user profiles.

✅ AI Integration for Wearable Technology

Implement on-device vs. cloud-based AI processing strategy for seamless user experience.
Collaborate with firmware & mobile app teams to ensure real-time responsiveness.
Optimize power consumption & memory efficiency for edge AI execution.

✅ Advanced AI & Multimodal Processing

Implement biometric AI, NLP (voice tone analysis), and movement-based pattern recognition.
Explore integration of adaptive AI models that improve accuracy over time.
Ensure AI is privacy-compliant, secure, and ethically responsible.

✅ Collaboration & Testing

Work closely with firmware engineers, UX/UI designers, and data scientists.
Develop AI testing protocols to validate model accuracy.
Optimize AI for fast execution on mobile and wearable platforms.

📌 Ideal Candidate Profile
💡 Expert in AI Development & Wearable Data Processing
💡 Proven experience in wearable AI, IoT, or real-time machine learning
💡 Strong knowledge of ML frameworks (TensorFlow, PyTorch, ONNX, etc.)
💡 Experience with Edge AI & power-efficient AI model optimization
💡 Familiar with AI ethics, bias reduction, and GDPR-compliant AI privacy

📌 Preferred Qualifications
🎯 Ph.D. or MSc in AI, Machine Learning, Neuroscience, or related fields
🎯 Experience in real-time multimodal AI (biometric + NLP + behavioral analysis)
🎯 Track record of AI deployment in embedded systems or mobile apps
🎯 Proven ability to optimize AI models for low-power devices

📌 Timeline & Budget
⏳ Project Start: ASAP
⏳ First AI Prototype: ~6 weeks
💰 Budget: Open to competitive proposals based on expertise

🚀 If you are a top AI developer passionate about pushing the boundaries of real-time AI & wearable integration, we’d love to hear from you!

📩 To Apply, Please Submit:
✅ Portfolio of AI projects (preferably related to biometric analysis or wearables)
✅ Your approach to real-time AI modeling & deployment
✅ Estimated timeline and budget for developing a first working prototype

Looking forward to working with the best in AI innovation! 🌍✨

Skills: AI Model Development, Face Detection, Image Classification, Unsupervised Learning, Supervised Learning, Deep Neural Network, Deep Learning, Artificial Intelligence, Machine Learning, Python

I'm looking for UIPath expert and certified years of experience and recent (optional but good) certification

Skills: Automation, Robotic Process Automation Software, UiPath, Document Automation, Web Scraping, Python, Microsoft Power BI, Microsoft Excel, Data Analysis, Tableau, SQL, Natural Language Processing, Deep Learning, Machine Learning, Computer Vision

Project Overview:



YolaFresh is seeking an experienced freelance data scientist to develop a robust demand forecasting model for fresh produce. The goal is to improve supply chain efficiency, optimize inventory management, and enhance predictability.



Key Responsibilities:

• End-to-End Forecasting: Manage the complete forecasting process including data processing, feature engineering, model selection, deployment, and iteration.

• Develop and implement a Daily Demand Forecasting Model tailored to fresh produce sales.

• Leverage state-of-the-art time-series forecasting techniques (e.g., Prophet, ARIMA, XGBoost, LSTM, etc.).

• Integrate external factors such as seasonality, weather conditions, and market trends into the model.

• Ensure the model achieves a WAPE of less than 10% (TBC by @Abderrahmane and team).

• Work closely with YolaFresh’s team to validate and refine forecasting accuracy.

• Deliver a scalable and interpretable model that can be integrated into YolaFresh’s operations.



Requirements:

• Experience: 6-8 years in data science with a strong focus on predictive modeling.

• Expertise in Forecasting Models: Hands-on experience with Prophet, ARIMA, LSTM, XGBoost, or other forecasting techniques.

• Strong Coding & Data Skills: Proficient in Python (Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch), SQL, and cloud-based data pipelines (Azure / GCP).

• Ability to understand business needs and translate them into actionable insights.



Nice-to-Have:

• Deep knowledge of fresh produce markets and their unique demand/supply dynamics.

• Familiarity with agriculture, logistics, or perishable goods forecasting challenges.



Project Duration & Engagement:

• Hybrid or Remote

• Duration: 6 weeks or less.

• Objective: Deliver a daily forecasting model with WAPE less than 10% within the project duration.

Skills: Data Science, Python, Machine Learning, Statistics, Data Mining, Deep Learning, Artificial Intelligence, Algorithm Development, Forecasting

I need an automated system that generates videos as the final output. There are two types of videos I’m looking for:

1. Zoom In/Out Videos

We use Midjourney’s Discord server to generate 2x zoomed images from an initial image.
This process is repeated around 100 times, resulting in a sequence of 100 progressively zoomed images.
These images are then compiled into a video using a GitHub script (see final outcome: GitHub - https://github.com/mwydmuch/ZoomVideoComposer).

2. Retexturing Videos

We use the EZGIF website to convert an existing import video into an image sequence (at least 1200px resolution and 20 FPS).
Each extracted frame is then processed through Midjourney’s edit/retexturing feature to generate AI-stylized variations.
Once retextured, the images are merged back into a video based on specific timing rules.

Project Goal:
Automate zoom-out video creation using Midjourney and a GitHub script.
Automate video retexturing, where an existing video is transformed frame-by-frame using Midjourney, then reassembled into a video.

Let me know if you have experience with Midjourney and are interested in this project. The pricing is fixed as mentioned in the task description. Most of the workflow involves existing tools where process needs to be done in loop, but I also need a script for merging images into a video (for Retexturing Videos part), as I couldn’t find one on GitHub.

Let's chat and I will send you examples of videos I am looking to make.

Skills: Artificial Intelligence, Python, Machine Learning, Deep Learning, Neural Network, TensorFlow

**Job Description:**

We are excited to announce an opportunity for an experienced AI developer to join our dynamic team, where you will play a crucial role in developing a sophisticated and robust model aimed at analyzing product reviews from various e-commerce platforms, including but not limited to Amazon and Shopify. This position is ideal for a candidate who is not only technically proficient but also deeply passionate about leveraging technology to improve online shopping experiences by ensuring the authenticity of customer feedback.

In this role, you will be tasked with utilizing advanced Natural Language Processing (NLP) techniques along with Machine Learning algorithms to effectively identify, analyze, and filter out fake or spam reviews that can mislead consumers and undermine the integrity of online marketplaces. Your expertise will enable us to build a system that is not only accurate but also scalable, accommodating the vast amount of data generated by e-commerce interactions.

The project requires a thorough understanding of data analysis, including the ability to preprocess, clean, and interpret large datasets, as well as a solid foundation in model training and evaluation. You will work closely with cross-functional teams, including data scientists, product managers, and UX/UI designers, to ensure that the detection system integrates seamlessly into our existing infrastructure and meets the needs of our users. Your contributions will directly impact customer trust and satisfaction, making your role vital to our mission.

We are looking for someone who is not only skilled but also innovative and eager to stay abreast of the latest developments in AI and machine learning. If you are motivated by the challenge of tackling complex problems and are passionate about ensuring that online customer feedback is authentic and trustworthy, we would love to hear from you!

**Key Responsibilities:**
- Design and develop a robust model for analyzing product reviews from e-commerce platforms.
- Utilize NLP techniques to extract meaningful insights from unstructured text data.
- Implement Machine Learning algorithms to identify patterns indicative of fake or spam reviews.
- Conduct thorough data analysis to improve model accuracy and performance.
- Collaborate with team members to integrate the detection system into our product offerings.
- Continuously monitor and refine the model based on real-world performance and user feedback.

**Required Skills:**
- Proficiency in Natural Language Processing (NLP).
- Strong understanding of Machine Learning principles and practices.
- Expertise in Data Analysis, including experience with statistical tools and methodologies.
- Proficient in programming languages such as Python or R.
- Experience working with e-commerce data and understanding its nuances.
- Excellent problem-solving abilities and attention to detail.
- Strong communication skills to convey complex technical concepts to non-technical stakeholders.

If you are ready to take on this exciting challenge and make a significant impact in the world of e-commerce, please submit your application, including your resume and any relevant project portfolios. We look forward to discussing how you can contribute to our team!

Skills: Machine Learning, Artificial Intelligence, Python, Deep Learning, Neural Network

**Job Description:**

We are looking for a skilled freelancer for Yolov8 object detection tasks. Your main responsibility will be to divide datasets into frames and ensure accurate labeling. Expertise in computer vision and Yolov8 is required. If you're detail-oriented with experience in object detection, please share examples of your previous work.

Skills: YOLO, Python, Machine Learning, TensorFlow, Computer Vision, Deep Learning

Problem: I have a custom multi-agent environment that isn't working correctly, there is a problem in either reward function or the setup because of which agents aren't learning the optimal behavior.

What I Need:
A thorough debugging AND correction of my code(wherever needed) to make the agents behave properly.

Software/Tools I’m Using:
Python
Stable-Baselines3(PPO)
Open AI Gym
Matplotlib, NumPy, etc.

Deliverables:
-Debugged code with changes that works properly.
-Brief notes on changes made and problems.

Skills: Python, TensorFlow, Machine Learning, Keras, Deep Learning

Python-based machine learning model that can classify metal material type in photos.

Skills: Python, Machine Learning, Artificial Intelligence, Deep Learning

We are looking for an experienced AI Developer / Machine Learning Engineer to conduct benchmarking tests on open-source vector databases used in Retrieval-Augmented Generation (RAG). The goal is to evaluate the impact of integrating a compressed “shadow” database on retrieval speed, LLM token efficiency, and search accuracy.

The ideal candidate has hands-on experience with vector databases, benchmarking AI models, and performance testing with structured queries. You will work with Qdrant, ChromaDB, Milvus, Faiss, and Weaviate, running tests to measure retrieval efficiency when using compressed vs. original text chunks.

📌 This is a benchmarking-only role. No model training or fine-tuning is required.

🛠️ Responsibilities:
✅ Design and execute benchmarking tests for vector retrieval performance in RAG databases.
✅ Measure retrieval latency, token reduction, and query accuracy when fetching compressed vs. original text.
✅ Implement automated scripts to fetch data from Qdrant, ChromaDB, Milvus, Faiss, and Weaviate.
✅ Optimize queries using vector search APIs, ANN indexes, and payload retrieval techniques.
✅ Store benchmarking results and generate comparison reports in Pandas / CSV format.
✅ Work with LLM tokenization models (e.g., GPT-3, GPT-4, T5) to measure token reduction.
✅ Deliver a structured final benchmarking report with insights and visual comparisons.

Skills: C++, Python, Machine Learning, Artificial Intelligence, Deep Learning, Retrieval Augmented Generation

I am looking for a partnership - I work for AWS and see first hand the value of AI and Generative AI. I am keen to look at building a Gambling Assistant chatbot that I will promote as a stand alone app / website / webapp. Idea being integration with a number of available relevant data sets, leverage open source AI Models to minimise initial costs.

Skills: Python, Tableau, Data Analysis, Data Science, Natural Language Processing, Generative AI, Machine Learning, Deep Learning, AI Chatbot, Large Language Model, Computer Vision, AI Agent Development, AI App Development, Retrieval Augmented Generation, Microsoft Power BI Data Visualization

We are seeking a skilled machine learning expert to develop and enhance a machine learning model tailored to our specific needs. The ideal candidate should have experience in model training, optimization, and deployment. You will be responsible for analyzing data, fine-tuning algorithms, and improving performance metrics. If you have a passion for transforming data into actionable insights and can deliver high-quality results, we want to hear from you!

Skills: Python, Machine Learning, Deep Learning, TensorFlow, Data Science

We are looking for an experienced AI Developer with strong proficiency in N8N and building AI voice agents. This role will focus on integrating AI solutions with our CRM (HubSpot), time tracking (Hubstaff), and data analytics platforms to streamline operations and enhance efficiency at Workspaceco Outsourcing.
This role is a full time position.

Responsibilities:

Develop and implement AI voice agents and automation workflows using N8N.
Integrate AI solutions with HubSpot CRM, Hubstaff time tracking, and data analytics platforms.
Collaborate with teams to identify automation opportunities and optimize workflows.
Test and deploy AI models; monitor performance and troubleshoot issues as needed.
Provide documentation and training to end-users on implemented solutions.
Requirements:

Proven experience as an AI Developer with expertise in N8N and building AI voice agents.
Strong proficiency in AI/ML frameworks (e.g., TensorFlow, PyTorch) and languages (Python).
Experience integrating AI solutions with HubSpot CRM, Hubstaff, and data analytics platforms.
Familiarity with natural language processing (NLP), machine learning, and deep learning techniques.
Excellent problem-solving skills and ability to work independently.
Good communication skills and a collaborative mindset.

Preferred Qualifications:
Knowledge of robotic process automation (RPA) tools.
Experience with cloud platforms (AWS, Azure, Google Cloud) and related AI services.

Contract Details:
Location: Remote
Hours: Full time - preference to be aligned with US (CST) timezone for co-work with our CEO
Rate: $20 per hour
How to Apply: Please submit your resume, portfolio (if applicable), and a brief cover letter outlining your experience with N8N, building AI voice agents, and integrating AI with CRM, time tracking, and analytics platforms.

Additional Notes:
Feel free to ask any questions you have about the position or our company in your application.
We look forward to reviewing your application and discussing this exciting opportunity with you!

Skills: API Integration, Artificial Intelligence, Python, API, Machine Learning

We are seeking a highly skilled Quantitative Developer and algorithmic programmer to help build, optimize, and deploy automated trading strategies. The ideal candidate will have expertise in Python, C++, machine learning, API-based execution, and real-time data analysis.

This is a long-term opportunity for an experienced quant developer looking to work and directly contribute to its trading performance.

⸻

Responsibilities

Algorithmic Trading & Execution
• Develop and deploy automated trading algorithms for MetaTrader 5 (MT5) and API-based platforms.
• Implement low-latency execution models, statistical arbitrage strategies, and liquidity-based trading.
• Optimize order execution to minimize slippage and market impact.

Quantitative Research & Strategy Development
• Research and implement AI-driven predictive models, machine learning strategies, and sentiment analysis.
• Work with macro-driven, high-frequency, and market-neutral strategies.
• Analyze order book data, dark pool activity, and institutional flow indicators.

Infrastructure & System Optimization
• Build data pipelines for real-time market data processing and backtesting.
• Implement risk management models to dynamically adjust trade exposure.
• Ensure system scalability, fault tolerance, and real-time monitoring.

⸻

Required Skills & Qualifications

Programming & Technical Skills

✅ Proficiency in Python, C++, or Rust for algorithmic trading system development.
✅ Experience working with MetaTrader 5 (MT5), FIX API, Interactive Brokers API, or other broker APIs.
✅ Strong background in machine learning, deep learning, and predictive modeling for trading.
✅ Knowledge of database architecture, cloud computing, and distributed systems.

Trading & Financial Market Knowledge

✅ Understanding of market microstructure, order flow dynamics, and execution algorithms.
✅ Experience with quantitative research, high-frequency trading (HFT), or systematic strategies.
✅ Familiarity with equities, FX, commodities, derivatives, and crypto trading.

Preferred Experience
• Experience at a hedge fund, proprietary trading firm, or investment bank.
• Knowledge of AI-powered trading models and NLP-based sentiment analysis.
• Experience deploying cloud-based trading systems (AWS, GCP, or Azure).
• Strong mathematical background in probability, stochastic processes, and time series analysis.

Skills: Python, Data Science, C++, Deep Learning, Machine Learning, Algorithm Development

I need a jsonl file that has thousands of AI prompts with human completions to train an AI humanizing program that I am creating using the OpenAI key. Basically we are trying to mimic humanize ai or stealthgpt. If you have experience in building jsonl files that can be used to get gptzero AI scores down to 0% let me know.

Skills: Python, Machine Learning, Neural Network, Artificial Intelligence, Deep Learning

I need a jsonl file that has thousands of AI prompts with human completions to train an AI humanizing program that I am creating using the OpenAI key. Basically we are trying to mimic humanize ai or stealthgpt. If you have experience in building jsonl files that can be used to get gptzero AI scores down to 0% let me know.

Skills: Python, Machine Learning, Neural Network, Artificial Intelligence, Deep Learning

will being doing a data analytic project using a kaggle database for Airline cancellation and delays, eventually leading to a predictive model and visualizations

Will need to find data
will being doing a data analytic project using a kaggle database for Airline cancellation and delays, eventually leading to a predictive model and visualizations

I am open to suggestions and making it more complicated

Skills: Python, Data Science, Machine Learning, Python Scikit-Learn, Deep Learning

Looking for a freelancer that can help us build an offline AI model that will be able to generate lifestyle background images for our bathroom and kitchen products.

Skills: Machine Learning, Deep Learning, Python, Artificial Intelligence, Adobe Illustrator, Artificial Neural Network, Computer Vision, Neural Network, TensorFlow, Keras

I am looking for a highly competent and ambitious AI expert to develop a custom Arabic text generation model using my Arabic dataset. The best approach—whether RAG, fine-tuning an LLM, or building a model from scratch—will be determined during our initial discussion.

This is a simple, personal project, but it provides a valuable opportunity to showcase your skills and abilities, with the potential to join a team working on larger and more complex projects in the near future.

Skills: Natural Language Processing, Artificial Intelligence, Python, Machine Learning, Deep Learning, GPT-4o, LLaMA, LLM Prompt Engineering, Problem Solving

Humano AI is developing a Massive Learning System (MLS) designed to train AI models capable of learning from real-world construction environments using advanced AI models, reinforcement learning (RL), and large-scale video-based training.

We specialize in data collection, data handling, and providing advanced AI training data to support the development of AI-driven humanoid workforces for the future of automation. Our focus is on AI model training, self-learning AI, and predictive intelligence derived from real-world video and sensor data.

We are looking for a team of highly skilled AI engineers to develop AI agents, neural networks, and reinforcement learning models that will allow AI systems to observe, learn, predict, and self-correct their tasks based purely on visual input and motion data.

This AI will be trained using real-world construction site video data, motion capture, and robotics AI to create autonomous AI systems capable of adapting, predicting, and continuously improving their understanding of human work processes.

Key Responsibilities

AI Model Development & Training
• Build neural networks & reinforcement learning models for AI-driven learning systems
• Implement self-learning AI that can improve from real-world experience
• Develop Multi-Modal AI (video-only training, integrating motion data & AI decision-making)
• Optimize NeuroSymbolic AI to allow AI systems to reason, correct errors, and adapt

Reinforcement Learning (RL) & AI Self-Learning
• Implement PPO, DQN, SAC, and other RL techniques to allow AI models to self-improve
• Develop AI-driven prediction models to optimize AI learning from real-world scenarios
• Train AI agents using Xsens motion capture, Metagloves, and real-world construction site footage

Computer Vision & AI for Motion Learning
• Develop pose estimation & motion tracking AI using OpenPose, YOLO, and vision-based AI
• Process video data from Xsens, Metagloves, Pupil Labs, and Intel RealSense depth cameras
• Optimize AI decision-making for real-world human motion learning & task automation

Large-Scale AI Infrastructure & Model Deployment (MLOps)
• Build scalable AI training pipelines for continuous AI learning
• Implement distributed AI training on AWS, GCP, or on-prem servers
• Optimize AI data processing using Apache Spark, Hadoop, and BigQuery
• Deploy AI models on Jetson, Raspberry Pi, and high-performance GPU clusters

Required Skills & Expertise
• AI & Machine Learning: Reinforcement Learning (PPO, DQN, SAC), Deep Learning (PyTorch, TensorFlow), AI Model Training, Transformer Models, NeuroSymbolic AI
• Computer Vision: OpenCV, YOLOv8, OpenPose, Pose Estimation, AI-Based Motion Tracking
• MLOps & AI Scaling: AWS SageMaker, Azure ML, Kubernetes, Docker, Apache Spark, Distributed AI Training
• Data Engineering & Processing: Apache Kafka, BigQuery, Hadoop, SQL, NoSQL, Vector Databases
• Programming Languages: Python, C++, TensorFlow, PyTorch, FastAPI, Flask, MATLAB
• AI Hardware Integration: Jetson Nano/Xavier, Intel RealSense, Xsens Motion Capture, Metagloves, LiDAR Sensors

Tools & Platforms We Are Using

AI Model Development & Training:
• Reinforcement Learning (PPO, DQN, SAC) for AI Self-Learning
• PyTorch, TensorFlow, OpenAI Gym, Stable-Baselines3, RLlib
• Computer Vision: OpenPose, YOLOv8, OpenCV, CNNs for Video-Based Learning

MLOps & AI Scaling:
• Cloud AI Training (AWS SageMaker, Google Vertex AI, Azure ML, Kubernetes)
• Distributed AI Training on GPU Clusters
• CI/CD Pipelines for AI Deployment, Model Versioning (GitHub Actions, Kubeflow, MLflow)

Big Data & AI Learning Infrastructure:
• Apache Spark, Kafka, Hadoop, BigQuery for Large-Scale AI Training
• Vector Databases (FAISS, Milvus, Pinecone) for AI Knowledge Storage

AI Hardware Integration & Embedded AI:
• Jetson Nano/Xavier, Raspberry Pi, Edge AI Processing
• LiDAR, IMUs, GPS for Real-World AI Decision Making

Preferred Qualifications
• Experience in reinforcement learning (RL) & AI model training for real-world learning
• Proven track record in scaling AI models for large-scale, real-world applications
• Experience in AI-powered motion tracking & pose estimation models
• Strong knowledge of video-based AI learning & self-correcting AI decision-making
• Familiarity with cloud-based AI training & distributed AI processing

Project Duration & Compensation
• Duration: Long-Term (6-12+ months, ongoing development & AI optimization)
• Budget: Competitive, based on experience. Open to fixed-price, hourly contracts, and full-time positions available
• Remote Work: Fully remote, with potential for future on-site testing & real-world AI data collection

If you are an AI expert, reinforcement learning specialist, or computer vision engineer looking to work on one of the most advanced AI training projects, we want to hear from you.

Skills: Reinforcement Learning, MLOps, Neural Network, Artificial Intelligence, Machine Learning, Computer Vision, TensorFlow, Deep Learning, Video Processing

Looking for someone who understands options and can create a program or AI-powered scanner to identify mispriced option spreads in real time. Please reply with which program you would use and your area of expertise.

Skills: AI Development, AI Bot, AI Trading, AI Builder, Python, C#, Artificial Intelligence, Machine Learning, Deep Learning, Quantitative Finance

Our firm is a woman-owned, minority-owned business specializing in data management, AI solutions, and technical consulting. We are building a talent pipeline for upcoming data-related projects in collaboration with government and enterprise clients. This is a future opportunity, contingent upon contract awards, and we are seeking qualified data professionals to join our talent pool.

If you are an experienced data engineer, data scientist, database administrator, or AI/machine learning specialist, we encourage you to express interest now to be considered for future positions.

Available Positions:
1. Data Engineer
📍 Responsibilities:

Design, develop, and maintain data pipelines, ETL processes, and cloud-based data architectures.
Work with structured and unstructured data, ensuring data integrity, security, and scalability.
Collaborate with data scientists, analysts, and software engineers to optimize data workflows.
📌 Preferred Skills:

Proficiency in Python, SQL, and cloud platforms (AWS, Azure, GCP).
Experience with ETL tools like Apache Airflow, Talend, or Informatica.
Knowledge of big data technologies (Hadoop, Spark, Databricks).
2. Data Scientist
📍 Responsibilities:

Develop and implement machine learning models and AI-driven analytics.
Perform statistical analysis, predictive modeling, and data visualization.
Work with large datasets to identify trends, patterns, and actionable insights.
📌 Preferred Skills:

Strong experience in Python, R, TensorFlow, and PyTorch.
Knowledge of NLP, computer vision, and deep learning frameworks.
Proficiency in data visualization tools (Tableau, Power BI, Matplotlib).
3. Data Analyst
📍 Responsibilities:

Analyze structured and unstructured data, creating detailed reports and dashboards.
Interpret complex datasets to support decision-making and business intelligence.
Work with stakeholders to identify data requirements and performance metrics.
📌 Preferred Skills:

Experience in SQL, Excel, and data visualization tools (Power BI, Tableau, Looker).
Strong analytical and problem-solving skills with experience in trend analysis.
Knowledge of data governance and compliance frameworks.
4. Database Administrator (DBA)
📍 Responsibilities:

Manage and maintain relational and NoSQL databases (PostgreSQL, MySQL, MongoDB).
Optimize database performance, security, and backup processes.
Ensure compliance with data privacy and security regulations.
📌 Preferred Skills:

Experience with SQL Server, Oracle, PostgreSQL, or MongoDB.
Understanding of database performance tuning and security best practices.
Familiarity with cloud-based database solutions (AWS RDS, Azure SQL, Google BigQuery).

Skills: Data Visualization, Microsoft Excel, Data Scraping, Data Mining

I am looking for an experienced developer or team to build an AI-powered cold-calling and customer service application similar to Bland.ai. The app should allow businesses to automate outbound calls, handle inbound inquiries, and engage in natural, human-like conversations using AI.

Key Features Required:
✅ AI-Powered Conversations – The app should use advanced speech recognition and text-to-speech (TTS) to enable natural-sounding AI interactions.
✅ API Integration – The system should support API connectivity to integrate with CRMs, databases, and other platforms.
✅ Real-Time Monitoring – Ability to monitor live calls and intervene if necessary.
✅ Voice Cloning & Customization – Users should be able to customize the AI voice to fit their brand.
✅ Low Latency & Cost Efficiency – The app should be optimized for fast response times and low operational costs.
✅ Analytics & Reporting – Provide insights on call performance, conversion rates, and other key metrics.
✅ Scalability – Support multiple users and high call volumes.

Tech Preferences (Open to Suggestions):
Speech Recognition: OpenAI Whisper, Google Speech-to-Text, or similar
TTS (Text-to-Speech): ElevenLabs, Amazon Polly, or custom TTS
AI Engine: OpenAI GPT, Claude AI, or custom NLP model
Backend: Python, Node.js, or other suitable stack
Frontend (if needed): React, Vue.js, or similar
Ideal Candidate:
Experience in AI-powered voice applications
Strong knowledge of speech recognition and TTS technologies
Ability to integrate APIs and build scalable architectures
Previous experience building customer service or cold-calling bots is a plus
Budget & Timeline:
Open to discussion based on the scope of work
Preferably looking for a MVP within 4-6 weeks
If you have experience in developing similar applications, please send:
1️⃣ Your relevant experience & portfolio
2️⃣ Your proposed tech stack & approach
3️⃣ Estimated cost & timeline

Looking forward to working with the right expert! 🚀

Skills: AI Agent Development, AI App Development, AI Bot, AI Development, Automatic Speech Recognition, Deep Learning, Artificial Intelligence, Python, Machine Learning, Natural Language Processing

🚀 AI/ML Developer - Computer Vision | Code the Future with Us!
Company: Roland Smart Shopping Cart 🛒

💡 Who Are We?
The world is changing, and we are redefining the retail industry with an AI-powered smart shopping experience! 🚀 At Roland Smart Shopping Cart, we are pioneering Turkey’s first-ever AI-powered smart shopping carts. Think of Amazon Go, but tailored for Turkey and global markets with a scalable and accessible approach.

Now, we are looking for a talented AI/ML Developer specialized in Computer Vision to join us in building this revolution!

🎯 Why Should You Join Us?
✅ Make a real impact: You won’t just write code; you’ll build technology that transforms real-world retail experiences.
✅ Be an engineer who makes a difference: Instead of just taking a job, you’ll be part of a groundbreaking startup shaping the future.
✅ Build the future today: Contribute to a project that will set the standard for major global retailers.
✅ A creative and flexible work environment: Work with a fast-moving, innovative, and dynamic team.
✅ Remote or hybrid work options.

🔍 Who Are We Looking For?
📌 Expertise in Computer Vision and AI/ML
📌 Hands-on experience with Python, OpenCV, TensorFlow, or PyTorch
📌 Experience in real-time object detection and tracking projects
📌 Knowledge of Edge AI solutions and optimization (Preferred)
📌 Passion for building new technology and a strong entrepreneurial mindset

If you’re excited about shaping the future of AI in the retail industry, you might be the perfect fit for our team! 🚀

Skills: PyTorch, Computer Vision, Python, Machine Learning, TensorFlow, OpenCV, Deep Learning, Artificial Intelligence, RESTful API, Object Detection & Tracking

Problem Statement
In the current enterprise networks that are deployed in organizations (SMB, Enterprise), there is a big
operational gap and challenges to manage the entire network architecture.
The Challenges
a) Management of multi-vendor environment
In today’s network world, organizations have multi-vendor network equipment and technologies. It is
difficult for the organizations to align resources who are well versed with all the technologies and
who can manage all of them.
For example, a network administrator might not be good at Aruba, but can be good at Cisco and vice
versa. This poses operational challenge to address issues where a person is not that aware about the
technology and if requirements such as upgrades, troubleshooting issues etc. comes up, then that
person is not able to cater to it or it will take time to learn new technology.
Configuration Management and Automation is something which is need of the hour.
b) Operational difficulties faced by network administrator
Network administrators face lot of challenges in understanding the issue, identification of issue
through reporting, troubleshooting and accurate resolution.
For example, if a user reports that web application hosted in data center is responding slowly. Then
as a traditional network administrator, he would have to check each and every hop (devices in the
path) till the data center and during this time, generate reports from each of the device to accurately
identify the issue.
This task becomes challenging and time consuming as well.
c) Effective Reporting
As a network engineer, architect or administrator, reporting is the key component that gives insights
into the data.
Currently, we have to login to each of the devices and depend upon what reports that particular
device presents and have to fetch those available reports and collate data to present to the
management.
For example, if management requirement is to provide a single report with:
• hostname of the endpoint
• user logged into the endpoint
• its mac address
• its IP address,
• its compliance status
• its profile
• how many times it got authenticated to network
• what did that user browse over the internet
• what attachments were shared over the email
To cater to this requirement, network administrator might have to login to multiple devices such as
ISE, firewall, proxy, email security gateway, endpoint protection logs etc. and then collate all the
information and present.
d) Asset Visibility and Classification
Core requirement of all the organizations is that what is connecting to my network, what type of
device it is and is it genuine device.
This functionality is provided by lot of vendors right now. However, either they are very expensive or
they are dependent on other technologies.
e) Network Architecture Design
There are many organizations, mostly SMB and in non-IT domain, where still the network
architecture is not designed as per recommended standards.
Flat networks, unmanaged switches, non-compliant security posture etc. are common in these type
of organizations.
f) Network and Network Security Compliances
Most of the organizations, who have standard network architecture do not have idea about what is
the compliance status of the devices, endpoints and all the different technologies that are in use.
For example, there are lot of outdated software versions running on switches.
g) Optimization
Most of the organizations are not aware about what actually their devices are capable of, both from
network infrastructure perspective as well as from network security perspective.
They have to rely on partners and vendors to determine best recommended practices. Still not all the
features are utilized.
For example, firewalls are not configured with optimum security features. Some of the important
security features might not have been configured which shall leave a security gap that an attacker
can leverage.
h) NOC and SOC capabilities
Currently, lot of organizations rely on outsourcing their SOC and NOC to third party vendors.
Even for basic incident response, organizations rely on other companies.
i) Total Cost versus actual requirement
In many cases, if organization needs to implement a specific use case, then they have to purchase the
entire license subscription as well as hardware or VMs.
For example, if an organization has a requirement of just asset visibility and classification, still, they
have to purchase whole suite / license of a particular vendor. For example, Solarwinds provides
visibility. But organization has to pay for a particular tier of licenses which has a small feature called
“Asset Visibility”.
Total cost of ownership increases here
j) Software development for existing Network technologies
Organizations might not have network software developers to cater to custom requirement within
their organizations.
For example, if an organization has requirement which needs API development, then it is not
possible due to lack of expertise
Proposed solution as an MVP (Both on-prem and SaaS based)
Nio Networks Inc. proposes a solution that shall address the above challenges phase wise. Below are
the phases and respective features that shall be developed:
1) Asset Visibility Module – As the name suggests, this module shall focus on development of
asset visibility module which shall accurately identify what is connected to an enterprise
network.
Development of network adapters, agents etc. that shall provide this accurate information is
the core task in this phase.
Timeline – 6 Months
2) Development of AI model – Once the Asset visibility is complete and we get data. Feed this
data to learn the network and optimize it.
Provide useful recommendations using the data available. For example, provide
notifications/suggestions to optimize customer network.
Timeline – 4 months
3) 4) 5) Reporting and Compliance check – Once the asset visibility is completed, develop a
reporting module. For example, multiple reports can be generated without much efforts
from network administrator.
This module shall also report non-compliant endpoints, devices etc. For example, this
module shall report if a particular endpoint is on latest patch or not.
Compliance reporting can be included here. For example, reporting for specific compliances
such as PCI-DSS, ISO 27001 etc.
Timeline – 4 months
Troubleshooting module – Since we have now an AI model trained for a specific network, it
can analyze and pin point any particular issue within the network and provide remediation
action.
Gradually, it can also remediate the issue itself.
Timeline – 5 months
Network Optimization and Network Designing Assitance – We can use the data to optimize
customer’s network and provide assistance in designing their network to make it more
structured / compliant
6) Timeline – 6 months
NOC / SOC capabilities module – Once the AI model is fully trained and is aware of the
network, it can trigger automated alerts for SOC and NOC, removing the need to outsource
NOC and SOC basic monitoring for the customer.
Timeline – 6 Months

Skills: AI Agent Development, AI Bot, AI Model Integration, React, Python, Machine Learning, Artificial Intelligence, API, Internet of Things, Deep Learning

Developer needed to train an image based dataset for object recognition and extraction.

The initial goal is to recognise and extract. However long term goals include generative ai and a recommendation system.

Currently I prefer a single freelancer to an agency due to cost factors and since I anticipate this to be a long term project (5-6) months with more milestones, thorough communication is required .

A complete understanding of the project and its goals is important.

Skills: Machine Learning, Python, TensorFlow, Deep Learning

Hey Upwork community!

I'm looking for a highly skilled specialist with deep expertise in OpenAI products to help develop an AI-driven sales system for my automotive business. The goal is to offload as many tasks as possible from my sales team, including lead generation, customer follow-ups, and deal closures.

I’d love to hear how you would approach this project and which OpenAI tools you’d use (e.g., GPT-4 for customer interaction, fine-tuned models for personalized sales pitches, and automation via OpenAI API).

To ensure you're a real person, please start your response with a fun fact about cars! Looking forward to your proposals. 🚀

Skills: AI Bot, Machine Learning, Artificial Intelligence, API, Python, Deep Learning