Manager, Software Engineering, Machine Learning

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.

At LinkedIn, our approach to flexible work is centered on trust and optimized for culture, connection, clarity, and the evolving needs of our business. The work location of this role is hybrid, meaning it will be performed both from home and from a LinkedIn office on select days, as determined by the business needs of the team.

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

• Hands on experience in data modeling and machine learning

• 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

• Published work in academic or industry forums

• 7+ years of industry experience

• Large-scale AI problem

• Technical background

• Strategic thinking

• Machine Learning, Big Data and Deep Learning

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 .

We seek candidates with a wide range of perspectives and backgrounds and we are proud to be an equal opportunity employer. LinkedIn considers qualified applicants without regard to race, color, religion, creed, gender, national origin, age, disability, veteran status, marital status, pregnancy, sex, gender expression or identity, sexual orientation, citizenship, or any other legally protected class.

LinkedIn is committed to offering an inclusive and accessible experience for all job seekers, including individuals with disabilities. Our goal is to foster an inclusive and accessible workplace where everyone has the opportunity to be successful.

If you need a Reasonable Accommodation to search for a job opening, apply for a position, or participate in the interview process, connect with us and describe the specific Accommodation requested for a disability-related limitation.

Fill out an Accommodation request here: https://app.smartsheet.com/b/form/b660a0327d044969abfd7a4e73d15c36

Reasonable accommodations are modifications or adjustments to the application or hiring process that would enable you to fully participate in that process. Examples of reasonable accommodations include but are not limited to:

• 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

A request for an accommodation will be responded to within three business days. However, non-disability related requests, such as following up on an application, will not receive a response.

LinkedIn will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by LinkedIn, or (c) consistent with LinkedIn's legal duty to furnish information.

Pursuant to the San Francisco Fair Chance Ordinance, LinkedIn will consider for employment qualified applicants with arrest and conviction records.

As a federal contractor, LinkedIn follows the Pay Transparency and non-discrimination provisions described at this link: https://lnkd.in/paytransparency.

Global Data Privacy Notice and Compliance Posters for Job Candidates

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.