Research Engineer, Applied AI Engineering

About This Role

This is a backend-focused software engineering role specializing in applying ML/AI to user-facing products. You will work on the systems that power OuterSignal’s AI/data pipeline: prompt chaining, eval design, research APIs, model routing, and prod orchestration. The evolution of this role will include inference serving, fine-tuning, and synthetic dataset generation.

What You’ll Do

• Build and improve production AI/data pipelines that run across LLMs, APIs, databases, and workflow systems like Temporal, Postgres, ClickHouse, and Kubernetes.
• Design evals and build Jupyter notebooks that help us measure model behavior, data quality, extraction accuracy, and end-to-end customer impact.
• Build observability into AI workflows so we can understand cost, latency, reliability, and quality.
• Experiment with new models, retrieval strategies, structured-output techniques, prompt/program architectures, and model-routing approaches.
• Integrate with fast-changing research and AI APIs, understand their behavior deeply, and build robust abstractions around them.
• Help define the foundation for future inference serving, fine-tuning, dataset generation, and model evaluation infrastructure.

Who You Are

• A strong engineer who can reason through distributed systems, data pipelines, databases, and are comfortable working across varying programming languages.
• You are extremely AI-fluent and actively use modern AI tools to move faster.
• You have strong first-principles thinking and can turn ambiguous problems into hypotheses, experiments, and shipped systems.
• You have good judgment and taste: you simplify aggressively, avoid unnecessary complexity, and care about maintainability.
• You care about measurement. You do not trust vibes when evals, tests, traces, or data can tell you what is actually happening.
• Bonus: You have experience with PyTorch, Hugging Face, vLLM, Ray, MLflow, RAG, fine-tuning & RL, inference serving, and/or model evaluation systems.