AI Engineer/ML Engineer - Senior Developers - AI Training - Jacksonville, US

Role overview This is a paid participant opportunity for senior AI and machine learning engineers based in Jacksonville to take part in large language model training and evaluation work. Engagement happens through structured, per-study tasks rather than a traditional employment arrangement, with compensation tied to the hours contributed. The work centers on applying rigorous technical judgment to model outputs, code, and reasoning traces used to train the next generation of AI systems.

Responsibilities - Assess AI-generated explanations of neural architectures, loss functions, and backpropagation for technical accuracy - Validate ML-specific code and notebooks, including training loops, preprocessing scripts, and evaluation routines, flagging inefficiencies and bugs - Supply structured human feedback that powers reinforcement learning from human feedback (RLHF) pipelines, helping align models with intent, safety, and helpfulness - Critically trace how models handle chain-of-thought prompts and identify where reasoning breaks down - Run comparative benchmarks of model outputs against defined taxonomies and performance metrics

Requirements - BS, MS, or PhD in Computer Science, Artificial Intelligence, Robotics, or a related quantitative discipline with a machine learning focus - Professional track record building, deploying, or fine-tuning ML models in production settings - Working command of neural network architectures including Transformers, CNNs, and RNNs, along with their optimization techniques - Hands-on experience with prompt engineering, RLHF, or retrieval-augmented generation (RAG) workflows - Ability to audit complex model logic, detect training data contamination, and evaluate the mathematical foundations of ML algorithms - Sharp attention to detail for spotting hallucinations, biased outputs, and logical failures in AI-generated technical content

Nice to have - Expert proficiency in PyTorch or TensorFlow and Keras - Advanced Python with NumPy, Pandas, and Scikit-learn, plus familiarity with Hugging Face Transformers - Experience with cloud ML platforms such as AWS SageMaker or Google Vertex AI, and tooling like Weights and Biases or LangChain - Familiarity with vector databases such as Pinecone, Milvus, or Weaviate for RAG evaluation

Benefits and work setup - Hourly compensation that can reach up to $80 depending on the study - Fully remote work with flexible hours - Brief 10 to 15 minute skills assessment followed by fast onboarding - Most tasks are designed to fit within about one hour of focused, uninterrupted work, with many shorter in length