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, model quality improvement, latency/cost tradeoff management, explainability, regression detection, drift detection
Preferred skills
LLM applications, model-assisted workflows, evaluation frameworks, human-in-the-loop ML, prompting, fine-tuning, retrieval, active learning, heuristics
Technologies
Python, Temporal, Postgres, AWS, LiteLLM
Responsibilities
Design evaluation frameworks for ambiguous tasks with partial or disputed ground truth; Build feedback loops turning review and correction into system improvements; Own production ML behavior end-to-end including precision/recall tradeoffs and drift detection; Partner with backend engineers to integrate inference into long-running workflows; Improve model quality using appropriate techniques like fine-tuning or active learning
Seniority
Senior, hands-on IC