Applied AI Research Engineer

Responsibilities

• Build reinforcement learning and agent environments for real customer and Frontier lab use cases, including task specifications, scoring, and evaluation.
• Develop benchmarks and evaluation harnesses to measure model and data quality across areas such as accuracy, robustness, safety, latency, and cost.
• Build LLM pipelines and agentic systems that support research, evaluation, and customer trials.
• Run fine-tuning, adapter, and other model experiments to evaluate how data and methods influence model behavior.
• Deploy local or self-hosted models for evaluation, inference, and automation workflows.
• Document experiments, configurations, data, results, and known limitations so other engineers can reproduce and build on your work.
• Partner with the GenAI
• Research team and cross-functional stakeholders to turn technical work into reusable assets for customer engagements.
• What You Bring
• Bachelor’s, Master’s, or PhD in Computer Science, Engineering, Machine Learning, or a related technical field.

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