Senior ML Engineer, Frontier Data Systems (In-Person)

Mercor; San Francisco (CA); On-site; USD 180,000 - 240,000; Full time

Benefits offered by this job

Bi-annual performance bonus

Equity grant

Relocation bonus

Housing stipend

Meals stipend

Equinox membership

Laundry reimbursement

Wellness reimbursement

Health, Dental, Vision insurance

Job summary

Mercor is building frontier AI data products in San Francisco, with in-person work five days a week across our SF, NYC, or London offices. We seek a driven ML product engineer who will design and deploy ML systems that score, validate, and improve complex work products where correctness is nuanced and labels are imperfect.

You will own production ML behavior end-to-end, addressing precision/recall, latency, and cost, while collaborating with backend engineers using Python, Temporal, Postgres,

Qualifications

• Shipping ML systems that improved a real product, workflow, or metric.
• Strong instincts for model quality, evaluation design, and production failure modes.
• Able to operate in ambiguous problem spaces with imperfect labels.
• Judgment on when to prompt, fine-tune, retrieve, or rely on human review.
• Solid engineering fundamentals across the ML stack.
• Familiarity with LLM applications or human-in-the-loop ML is a plus.

Responsibilities

• Build ML systems that score, validate, and improve complex work products.
• Design evaluation frameworks for ambiguous tasks.
• Create feedback loops from review, disagreement, correction, and adjudication into model improvements.
• Own production ML behavior end-to-end: precision/recall, drift, latency, cost, and explainability.
• Collaborate with backend engineers to integrate inference into durable, long-running workflows.

Skills

ML systems

Evaluation design

Production failure modes

Prompting

Fine-tuning

Retrieval

Human-in-the-loop

Engineering fundamentals

Tools

Python

Temporal

Postgres

AWS

LiteLLM

Job description

Mercor is building frontier AI data products in San Francisco, with in-person work five days a week across our SF, NYC, or London offices. We seek a driven ML product engineer who will design and deploy ML systems that score, validate, and improve complex work products where correctness is nuanced and labels are imperfect.

You will own production ML behavior end-to-end, addressing precision/recall, latency, and cost, while collaborating with backend engineers using Python, Temporal, Postgres,