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Manager, Software Engineering, Machine Learning

$170K–$277KFull-time · Mountain View, CA
✓ Verified live on the employer's own system · added 8 days ago
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Mid-level · 5+ yrs exp

Requirements

Education: Bachelor's degree or related field

Experience: 5+ years

Skills & tools

Machine LearningHiringTeam LeadershipProcess ImprovementManagementProgrammingTranslation

Benefits — mentioned in this posting

Wellness & perksBonus / commission
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Full job description

The AI Agent Platform & Expertise Graph Team is a self-embedded group of application engineers and AI engineers building the core agentic platforms and product features that power LinkedIn's hiring and job-seeker experiences. We sit at the intersection of applied AI and product engineering, owning systems end-to-end from foundational platforms to member-facing experiences.

We're building LinkedIn's Expertise Graph, a new long-term moat that lets professionals demonstrate expertise once and reuse it everywhere, and a new AI Assessment Platform powering AI interviews and skill assessments across LinkedIn hiring and seeker products. We're looking for an engineering leader to build and grow this team and drive both bets end-to-end.

You bring strong AI depth that guides architecture across agentic systems, LLMs, and ML platforms, paired with sharp product sense to translate ambiguous, high-stakes problems into experiences members love. You've built and scaled high-performing teams, set technical direction in fast-moving domains, and thrive partnering with product, design, and other cross-functional teams.

Most of all, you're energized by owning a defining, greenfield bet that reshapes how the world hires.

Manage and grow a high-performing team of researchers/applied scientists, and engineers. Attract, mentor, and develop diverse talent while fostering an inclusive, collaborative environment where people feel empowered to share ideas, take smart risks, and grow into technical leaders.

Translate product and business needs into a clear, focused technical roadmap. Ensure the team’s day-to-day work aligns with LinkedIn’s mission and long-term priorities. Partner with senior leadership to shape long-range AI and infrastructure strategy.

Collaborate with infrastructure and platform teams retrieval and serving system performance optimizations through advanced techniques like GPU-powered retrieval-as-ranking optimization, adaptive caching, and parameter-efficient fine-tuning. Maintain high standards for reliability, scalability, and latency.

Work closely with partner teams to identify shared opportunities, align on long-term goals, and maintain consistent progress. Address misalignments proactively with clarity, empathy, and data-driven reasoning.

Create a culture that encourages experimentation, curiosity, and continuous improvement. Ensure the team adheres to strong engineering and scientific practices, enabling rapid iteration through A/B testing and rigorous evaluation.

  • BA/BS in Computer Science or other technical discipline, or related practical technical experience
  • 1+ year(s) of management experience or 1+ year(s) of staff level engineering experience with management training
  • 5+ years of related industry experience in software design, development, and algorithm related solutions
  • 1+ years of experience in software engineering/technical engineering management and people management
  • 1+ year(s) of management experience or 1+ year(s) of staff level engineering experience with management training
  • Master’s degree in Computer Science, Information Retrieval, Machine Learning, Natural Language Processing, or a related field
  • Ph.D. in Computer Science, Information Retrieval, Machine Learning, Natural Language Processing, or a related discipline
  • Strong technical background and experience leading teams in Machine Learning, LLMs, Retrieval systems, Large-model optimization, On-device ML
  • Experience designing and deploying large-scale recommender systems

We strongly believe in the well-being of our employees and their families. That is why we offer generous health and wellness programs and time away for employees of all levels.

LinkedIn is committed to fair and equitable compensation practices. The pay range for this role is $170,000 to $277,000. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to skill set, depth of experience, certifications, and specific work location.

This may be different in other locations due to differences in the cost of labor.

The total compensation package for this position may also include annual performance bonus, stock, benefits and/or other applicable incentive compensation plans. For more information, visit https://careers.linkedin.com/benefits .

  • Documents in alternate formats or read aloud to you
  • Having interviews in an accessible location
  • Being accompanied by a service dog
  • Having a sign language interpreter present for the interview

Please use this link to access documents that provide information about how LinkedIn handles the personal data of employees and job applicants, as well as the E-Verify Participation Notice and the Department of Justice Immigrant and Employee Rights Section Right to Work posters: https://www.linkedin.com/legal/candidate-portal.

Basic

  • BA/BS in Computer Science or other technical discipline, or related practical technical experience
  • 1+ year(s) of management experience or 1+ year(s) of staff level engineering experience with management training
  • 5+ years of related industry experience in software design, development, and algorithm related solutions
  • 1+ years of experience in software engineering/technical engineering management and people management
  • 1+ year(s) of management experience or 1+ year(s) of staff level engineering experience with management training
  • Master’s degree in Computer Science, Information Retrieval, Machine Learning, Natural Language Processing, or a related field
  • Ph.D. in Computer Science, Information Retrieval, Machine Learning, Natural Language Processing, or a related discipline
  • Strong technical background and experience leading teams in Machine Learning, LLMs, Retrieval systems, Large-model optimization, On-device ML
  • Experience designing and deploying large-scale recommender systems

We strongly believe in the well-being of our employees and their families. That is why we offer generous health and wellness programs and time away for employees of all levels.

LinkedIn is committed to fair and equitable compensation practices. The pay range for this role is $170,000 to $277,000. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to skill set, depth of experience, certifications, and specific work location.

This may be different in other locations due to differences in the cost of labor.

The total compensation package for this position may also include annual performance bonus, stock, benefits and/or other applicable incentive compensation plans. For more information, visit https://careers.linkedin.com/benefits . Team

The AI Agent Platform & Expertise Graph Team is a self-embedded group of application engineers and AI engineers building the core agentic platforms and product features that power LinkedIn's hiring and job-seeker experiences. We sit at the intersection of applied AI and product engineering, owning systems end-to-end from foundational platforms to member-facing experiences.

We're building LinkedIn's Expertise Graph, a new long-term moat that lets professionals demonstrate expertise once and reuse it everywhere, and a new AI Assessment Platform powering AI interviews and skill assessments across LinkedIn hiring and seeker products. We're looking for an engineering leader to build and grow this team and drive both bets end-to-end.

You bring strong AI depth that guides architecture across agentic systems, LLMs, and ML platforms, paired with sharp product sense to translate ambiguous, high-stakes problems into experiences members love. You've built and scaled high-performing teams, set technical direction in fast-moving domains, and thrive partnering with product, design, and other cross-functional teams.

Most of all, you're energized by owning a defining, greenfield bet that reshapes how the world hires.

Manage and grow a high-performing team of researchers/applied scientists, and engineers. Attract, mentor, and develop diverse talent while fostering an inclusive, collaborative environment where people feel empowered to share ideas, take smart risks, and grow into technical leaders.

Translate product and business needs into a clear, focused technical roadmap. Ensure the team’s day-to-day work aligns with LinkedIn’s mission and long-term priorities. Partner with senior leadership to shape long-range AI and infrastructure strategy.

Collaborate with infrastructure and platform teams retrieval and serving system performance optimizations through advanced techniques like GPU-powered retrieval-as-ranking optimization, adaptive caching, and parameter-efficient fine-tuning. Maintain high standards for reliability, scalability, and latency.

Work closely with partner teams to identify shared opportunities, align on long-term goals, and maintain consistent progress. Address misalignments proactively with clarity, empathy, and data-driven reasoning.

Create a culture that encourages experimentation, curiosity, and continuous improvement. Ensure the team adheres to strong engineering and scientific practices, enabling rapid iteration through A/B testing and rigorous evaluation.

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