Staff AI/Machine Learning Engineer
Core
Design and build production ML systems for generating synthetic environments, de-identifying enterprise data, and evaluating frontier AI agents.
Role type
Staff AI/Machine Learning Engineer (Synthetic Data & Evaluation)
Builds
Synthetic training environments, de-identified datasets, and agent evaluation infrastructure
Domain
AI Infrastructure, Synthetic Data, Enterprise Data Privacy
Deliverable
production ML models
Required skills
LLMs, agents, RL, NER, information extraction, generative/synthesis models, distributed training, PyTorch, software engineering fundamentals, model evaluation (precision/recall/utility), inference optimization
Preferred skills
synthetic data generation, data privacy/de-identification, benchmark construction
Responsibilities
Design systems for longitudinally coherent synthetic environments; build synthesis models for realistic data replacement; train and improve NER models for entity detection; build evaluation infrastructure for agent outcomes; fine-tune open-weight models on generated data; expand coverage into new domains and languages; optimize inference for sensitive data; partner with frontier labs and enterprise teams
Seniority
Staff, hands-on IC with strategic impact
