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

Role overview Senior AI and machine learning engineers in the Indianapolis area can contribute to large language model training and evaluation through this paid, task-based participant opportunity. Participants apply deep technical expertise to audit, rate, and refine model outputs on a per-study basis. The core mission is supplying the high-quality human feedback that modern alignment and evaluation pipelines require.

Responsibilities - Review AI-generated explanations of neural architectures, loss functions, and backpropagation for technical accuracy - Audit ML code and notebooks, including training loops, preprocessing scripts, and evaluation routines, flagging inefficiencies and bugs - Deliver structured feedback that fuels reinforcement learning from human feedback (RLHF) workflows aimed at improving model safety and helpfulness - Trace how a model navigates chain-of-thought prompts and pinpoint where its reasoning breaks down - Benchmark competing model outputs against defined technical 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 - Production experience building, deploying, or fine-tuning ML models - Solid grasp of neural network architectures such as Transformers, CNNs, and RNNs, along with optimization techniques - Hands-on experience with prompt engineering, RLHF, or retrieval-augmented generation (RAG) systems - Capacity to audit complex model logic, detect training-data contamination, and assess the mathematical foundations of ML algorithms - Keen eye for 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 experience using Hugging Face Transformers - Familiarity with cloud ML platforms such as AWS SageMaker or Google Vertex AI, and tooling like Weights and Biases or LangChain - Experience with vector databases such as Pinecone, Milvus, or Weaviate

Benefits and work setup - Hourly compensation that can reach up to $80 depending on the study - Fully remote work with flexible scheduling - Short 10 to 15 minute skills assessment followed by quick onboarding - Most tasks are designed to fit within roughly one hour of uninterrupted work, with many being shorter