Machine Learning Engineer, Frontier Data Products
Core
Build ML systems that score, validate, and improve complex work products where correctness is nuanced and labels are imperfect.
Role type
Senior IC machine learning engineer (applied ML product engineering)
Builds
Frontier Data Products infrastructure for scoring, validating, and improving complex work products
Domain
AI data / Frontier AI models / Human-in-the-loop systems
Deliverable
production ML models
Required skills
ML system design, evaluation framework design, error analysis, production failure mode analysis, precision/recall tradeoff management, regression detection, drift detection, latency optimization, cost optimization, explainability, model quality improvement, prompting, fine-tuning, retrieval, active learning, heuristics, backend integration
Preferred skills
LLM applications, model-assisted workflows, evaluation frameworks, human-in-the-loop ML
Technologies
Python, Temporal, Postgres, AWS, LiteLLM
Responsibilities
Build ML systems for scoring and validating complex work products with imperfect labels; Design evaluation frameworks for ambiguous tasks with partial or disputed ground truth; Build feedback loops converting review and correction into system improvements; Own production ML behavior including precision/recall tradeoffs and drift detection; Improve model quality using appropriate techniques like fine-tuning or retrieval; Partner with backend engineers to integrate inference into long-running workflows
Seniority
Senior, hands-on IC