Applied AI Research Engineer

• 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 accuracy, robustness, safety, latency, and cost
• Build LLM pipelines and agentic systems supporting 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 for reproducibility
• Partner with the GenAI Research team and cross-functional stakeholders to turn technical work into reusable customer-engagement assets

• Bachelor’s, Master’s, or PhD in Computer Science, Engineering, Machine Learning, or a related technical field
• 3+ years of professional engineering or relevant industry experience in AI/ML or software engineering
• Strong software engineering skills and experience building reliable, maintainable AI systems
• Hands-on experience building agentic systems, reinforcement learning environments, LLM pipelines, or similar AI systems
• Experience building evaluation harnesses, benchmarks, or model testing pipelines
• Ability to work independently on technical problems and move quickly from an idea or research question to a working solution
• Strong understanding of experimentation, reproducibility, and technical documentation

• Flexible work arrangements
• Tools, resources, and development opportunities to build capability
• Opportunity to work on complex AI challenges across industries and geographies
• Collaborative culture emphasizing innovation, accountability, curiosity, and excellence