Machine Learning Engineer
Build production ML systems for measuring, predicting, and scaling data quality for frontier AI models. Requires 3-6 years experience in applied ML or related production systems (ranking, recommendations, data quality, fraud) plus strong software engineering skills.
About the job
Responsibilities
- Build ML and data systems that help measure quality across complex human data workflows
- Develop systems for expert matching, quality prediction, and anomaly detection
- Build evaluation infrastructure for tasks, reviewers, projects, and data deliveries
- Turn messy real-world signals into models, metrics, and product improvements
- Partner with engineers, domain experts, and operators to improve how high-quality data is created and reviewed
- Own high-impact systems from early design through production deployment
Requirements
- 3-6 YOE with relevant experience
- Strong software engineering background with experience shipping production systems
- Experience with applied ML, ranking, recommendations, search quality, marketplace systems, trust/safety, fraud, or data quality systems
- Strong data intuition and ability to work with messy, ambiguous real-world signals
- Comfort working across backend systems, data pipelines, ML models, and internal tools
- Ability to move quickly in a high-ownership, fast-changing environment
- Deep care for quality, precision, and customer impact
Not a Fit If
- You want to do pure research without owning production systems
- You only want to train models and not build product infrastructure
- You need clean datasets and perfectly scoped problems
- You do not want to work closely with users, operators, and domain experts
Skills
Machine Learning, Applied Ml, Ranking, Recommendations, Search Quality, Data Quality Systems, Backend Systems, Data Pipelines, Production Systems, Anomaly Detection, Quality Prediction, Expert Matching
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