Machine Learning Engineer
Core
Building agentic harnesses, data integrations, APIs, and evaluation systems to help researchers and scientific teams make evidence-backed decisions using language models.
Role type
Senior IC Machine Learning Engineer (Product & Systems)
Builds
Agentic workflows for evidence synthesis, enterprise APIs, evaluation systems, and trust/transparency features for model outputs.
Domain
Scientific research, literature analysis, and decision-support systems using LLMs.
Deliverable
production ML models | product features | infrastructure
Required skills
End-to-end software engineering, language model reasoning (prompting, retrieval, evals), product sense, backend/data/model layer mobility, coding assistant proficiency
Preferred skills
Experience with ambiguous problem solving, rapid shipping of user-facing features, building new software paradigms enabled by LLMs
Technologies
Python, transformers, generic types, decorators, coding assistants
Responsibilities
Build interfaces and artifacts to help users trust and act on model outputs; combine language models with external tools and retrieval systems; build evaluation systems to measure user outcome improvements; develop agentic harnesses for assessment and experiment planning; improve extraction and search quality via system design or finetuning.
Seniority
Senior, hands-on IC