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As a Machine Learning Engineer at Mercor, you’ll operate at the intersection of backend engineering and applied machine learning. ML Engineers at Mercor are generalists first, shipping production systems that power performance prediction, search, recommendation, and fraud detection while also bringing statistical and modeling rigor where it matters. The work spans everything from building APIs and infrastructure to training and deploying models, always tied closely to core product outcomes. You’ll collaborate with product engineers and operations to deliver systems that directly impact how companies source talent and how candidates find opportunities
Job Responsibility:
Research, train, and productionize ML models for engagement prediction, scoring, search
Build backend infrastructure and APIs to serve ML models reliably at scale
Run experiments, analyze results, and iterate quickly to improve both models and product performance
Work cross-functionally with Operations and Product to translate business needs into model-driven solutions
Wear many hats: from backend engineer to applied ML practitioner to product problem-solver
Requirements:
Strong backend engineering skills (ex. Python/Django or similar) plus a solid foundation in applied ML and statistics
Proven experience shipping production systems or ML-driven products end-to-end
High ownership and comfort operating in ambiguous, fast-changing environments
Generalist mindset: willing to flex between backend, modeling, data pipelines, and product problem-solving
What we offer:
Generous equity grant vested over 4 years
A $20K relocation bonus (if moving to the Bay Area)
A $10K housing bonus (if you live within 0.5 miles of our office)