Applied AI Research Engineer
Position Summary & Responsibilities
About the Role
As an Applied Research Engineer, you’ll build practical AI research assets that support Frontier lab initiatives and customer engagements. This is an implementation-focused role for someone who enjoys turning research concepts into working systems.
You’ll work with a high degree of autonomy, experimenting with new approaches and developing solutions that can be reused across customer opportunities. You’ll partner closely with the GenAI Research team and cross-functional stakeholders to bring technical ideas into practical applications.
Your Impact
- 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
Key Role Competencies & Evaluation Highlights
Focuses on global scalability, meticulous management of distributed human-in-the-loop workforces, and AI data quality control.
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