Mercor5 days ago

Product Operations Manager, Research Services

Salary not specified

MARKET

65,900 ₽median for this role

AI Researcher · 37 jobs with disclosed pay

5,600half of the offers: 16,833–78,900143,300

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Responsibilities

01Prioritize the Benchmark Portfolio: Own the intake and prioritization of new benchmarks and evaluations supported in our platform. Weigh customer demand, observed capability gaps, differentiation versus public benchmarks, and build cost to inform our priorities.
02Support Dataset Demand Generation: Run and share leaderboard evals to drive Mercor’s research brand equity during new model releases.
03Manage Training and Inference Partners & Budgets: Own the relationships with our inference providers, compute partners, and external training vendors. Forecast capacity against the delivery calendar, negotiate and track SLAs and rate cards, monitor cost per eval run and per rollout, and qualify new partners before we need them.
04Track Customer Delivery: Maintain the operating picture across every active evals, loss analysis, and post-training engagements, highlighting scope, milestones, dependencies, and SLA status. Run the delivery review, escalate slipping commitments before the customer notices, and give research counterparts a straight answer on where things stand.
05Shape the Product: Translate recurring delivery friction into product requirements for the eval platform and partner with Engineering to automate the workflows you'd otherwise be running by hand.

01Experience: 3+ years in Product Operations, Product Management, Technical Program Management, Research Operations, Solutions Engineering, or a similar technical, customer-facing role. Experience operating in an ML research or AI infrastructure environment strongly preferred.
02Technical Fluency: Fluent in how modern LLM evaluation works, including harness design, verification, agentic rollouts, and contamination and fairness pitfalls. Working understanding of post-training (SFT, preference ranking, RL) and of inference economics. Familiar with coding agents; comfortable in SQL and Python without agent assistance.
03Vendor and Capacity Judgment: Can plan capacity against an uncertain demand curve, hold partners to an SLA, and weigh cost against reliability without needing to escalate every call.
04Ownership: Thrive in ambiguous environments and take ownership from problem definition through execution. Comfortable being the person accountable for a date.
05Communication: Can hold your own in a technical conversation with AI researchers and write a status update an executive can act on. Excellent written and verbal communication.
06Systems Thinking: Strong project management and cross-functional coordination skills. Passion for fixing problems at the source and building repeatable systems rather than one-off solutions.