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Applied ML Manager

Speak

full-time

Posted on:

Location Type: Hybrid

Location: San FranciscoCaliforniaUnited States

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Salary

💰 $250,000 - $300,000 per year

Job Level

About the role

  • Manage and grow the ML team through clear expectations, regular feedback, and strong coaching.
  • Define quarterly ML goals and success metrics, establish baselines, and build a visible “scoreboard” for progress.
  • Drive end-to-end execution on key ML initiatives: planning, evaluation, iteration, rollout, and impact measurement.
  • Build a repeatable model evaluation and experimentation process (quality, performance, reliability), including rollout criteria.
  • Partner with Product and Engineering leaders to align roadmaps, clarify ownership, and ensure ML work is shippable and predictable.
  • Identify gaps in our current ML strategy, propose concrete bets, and translate direction into actionable plans.
  • Help hire thoughtfully as the team grows, without prematurely scaling into a large org.

Requirements

  • 8–10+ years overall experience in applied ML, with a track record of shipping ML and LLM systems into production.
  • 4+ years people management experience, including leading 1:1s, giving feedback, and handling performance.
  • Strong technical judgment in applied ML (not primarily ML infra/MLOps), including ability to define and run rigorous evaluations.
  • Excellent metric sense and analytical thinking: can translate ambiguous goals into measurable outcomes and make tradeoffs.
  • Strong cross-functional collaboration skills with Product, Engineering, and Design.
  • Clear written communication: can write crisp strategy docs, decision memos, and goal docs.
  • Bonus: speech/audio, linguistics, or multimodal experience.
Benefits
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Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools
machine learninglarge language modelsmodel evaluationexperimentation processimpact measurementdata analysisperformance evaluationmetric definitionrigorous evaluationsapplied ML
Soft Skills
people managementcoachingfeedbackanalytical thinkingcross-functional collaborationwritten communicationstrategic thinkinggoal settingperformance handlingclarity in expectations