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 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 AI-driven decision support.
Required skills
End-to-end software engineering, language model prompting and reasoning, retrieval systems, evaluation design, system architecture, product sense.
Preferred skills
Experience with agentic workflows, fine-tuning strategies, building user-facing AI products, using coding assistants effectively.
Technologies
Python, transformers, retrieval systems, APIs, data integrations.
Responsibilities
Build agentic harnesses for target assessment and experiment planning; develop data integrations across scientific databases and customer systems; create evaluation systems to measure user outcomes; design trust and transparency features for model outputs; build enterprise APIs and structured-output pipelines.
Seniority
Senior, hands-on IC
