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

Role overview This is a paid, task-based research opportunity for experienced machine learning engineers who want to shape the next generation of large language models. Participants work remotely on focused assignments that involve auditing, evaluating, and refining AI outputs using deep technical judgment. Engagement is flexible and intermittent, designed to fit alongside other professional commitments.

Responsibilities - Review AI-generated explanations of model architectures, loss functions, and backpropagation for technical accuracy - Audit ML code, training scripts, and evaluation notebooks for correctness and efficiency - Provide structured human feedback used to align models through reinforcement learning from human feedback workflows - Critically analyze chain-of-thought reasoning and surface logical failures or hallucinations - Run comparative benchmarks across model outputs using defined technical taxonomies and metrics

Requirements - Bachelor's, Master's, or PhD in Computer Science, Artificial Intelligence, Robotics, or a related quantitative field with a machine learning focus - Professional experience building, deploying, or fine-tuning ML models in production - Strong command of neural network architectures such as Transformers, CNNs, and RNNs, plus modern optimization techniques - Hands-on work with prompt engineering, RLHF, or retrieval-augmented generation pipelines - Sharp analytical eye for spotting biased outputs, training data contamination, and faulty reasoning - Located in the Baltimore area

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

Benefits and work setup - Compensation typically up to $80 per hour for qualifying tasks - Fully remote with flexible, task-based scheduling - One-hour focused sessions, with many assignments shorter in duration