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Director, Enterprise Machine Learning & Research

External
Scale AI logoScale Ai · San Francisco, CA
$290K–$362K/yrFull-timeOn-site2w ago
Deep LearningLeadershipMachine LearningPrototypingStakeholder Management
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About the role

At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Yo

Responsibilities

  • Lead, mentor and grow a team of research scientists and engineers working on GenAI research initiatives (e.g., evaluation, post-training, agents, RL environments).
  • Define and drive a multi-year research roadmap: identify key scientific questions, set milestones, allocate resources, and ensure rigorous execution.
  • Collaborate cross-functionally with engineering, product, client-facing teams and external academic or industry partners to translate research into components, insights, and actionable outcomes.
  • Communicate compellingly: publish research, present at conferences, engage in open-source contributions, and represent the team externally.
  • Drive an inclusive, high-performing culture: help your team through technical challenges, provide growth opportunities, and attract top talent.
  • Stay deeply connected to the research community, understanding major trends, and helping set them.
  • Thrive in a high-energy, fast-paced startup environment and are ready to dedicate the time and effort needed to drive impactful results.

Requirements

  • Core Qualifications
  • 8+ years of hands-on research experience (PhD or equivalent preferred) in machine learning, deep learning, generative models, agent/rl systems or related domains.
  • A strong track record of research excellence, including publications in top-tier ML/AI venues (NeurIPS, ICML, ICLR, ACL, etc.).
  • Experience and track of recording in landing major research impacts in a fast-paced environment
  • Experience leading or managing research teams. You're excited to mentor, coach and develop talent.
  • Excellent written and verbal communication skills. You are able to articulate research ideas and outcomes to both technical and non-technical stakeholders.
  • Exceptional communication and stakeholder management skills, with the ability to influence executives, customers, and cross-functional partners
  • Hands-on experience building and deploying agent-based, tool-augmented, or workflow-driven LLM systems in enterprise environments
  • Prior ownership of enterprise AI platforms, internal ML products, or customer-facing AI services at scale
  • Proven track record of partnering directly with enterprises to identify high-impact use cases and deliver measurable business outcomes
  • Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is:
  • $289,800 - $362,250 USD
  • PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants.

Benefits

Health insuranceDental insuranceVision insurancePaid time offEquity / stock options

Additional Information

The Enterprise ML team works on the front lines of the AI revolution, partnering deeply with customers to identify high-impact business problems and build cutting-edge AI systems using Scale's proprietary research, data, and infrastructure-unlocking domain expertise through high-quality data and expert feedback. As Director of Enterprise ML, you will lead a world-class team of research scientists and engineers, define the research roadmap, and drive execution from early prototyping to deployment. You'll thrive in a fast-moving environment, balancing deep technical leadership with people management, vision setting, and delivery. This role is ideal for a leader who thrives in ambiguity, understands both frontier GenAI capabilities and their limitations, and is motivated by turning research into durable, production-ready systems.


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