Staff AI Engineer

About the role

This role will be based in Sunnyvale, San Francisco, or New York City. 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.

Responsibilities

• AI is at the core of how LinkedIn connects more than a billion members to opportunity across jobs, sales, marketing, content, and trust platforms.
• As a Staff AI Software Engineer you will own end-to-end machine learning systems that run in production at LinkedIn scale.
• You won't just train models, you will own the recommender and classification system that power LinkedIn's core products.

Your responsibilities cover the full product lifecycle from translating product requirements into system design, training the models to power the system, driving the experiments that prove efficacy, and managing the GPU fleets that run them at scale in milliseconds - you are the engine that drives value for our members.

This is a lead individual-contributor role; we expect you to own all aspects of a significant workstream, align technical direction across orgs, and lead the day to day work of engineers on your own team. As owner you have the freedom to set technical directions and are held accountable for delivering measurable member and business impact with a sense of urgency.

What success looks like in your first year

• You lead a significant AI workstream end to end and ship at least one model-based system to a measured impact on member or business value and effectively communicate the impact to external partners.
• You become the go-to cross-team point of contact for your domain and onboard or mentor at least one other engineer onto the stack.
• You drive a meaningful efficiency or quality improvement (i.e. inference/training efficiency, engineer velocity, or tech-debt removal) involving multiple members of the team backed by data.
• You operate systems reliably as on-call and root-cause at least one significant production regression.

Basic Qualifications

• Bachelor's degree in Computer Science or related technical field or equivalent practical experience
• 4+ years of industry experience in software design, development, and algorithm related solutions.
• 4+ years experience in programming languages such as Java, Python, etc.
• 4+ years experience with machine learning, data mining, and information retrieval or natural language processing

Preferred Qualifications

• 6+ years of relevant AI/Machine Learning experience
• MS or PhD in Computer Science or related technical discipline
• Experience leading a significant project of 3+ AI engineers
• Experience with cross-functional communication to product, engineering, business or data science partners.
• Experience with PyTorch or similar Deep Learning frameworks
• Experience with Spark for data manipulation and transformation
• Experience with A/B testing at scale in a consumer-facing product
• Experience with AI code development (i.e ClaudeCode, Codex, Copilot)
• Experience adapting pre-trained LLMs to production systems including fine-tuning and student-teacher model paradigms
• Experience applying AI/ML to recommender systems at scale
• Published work in academic conferences or industry circles.

Suggested Skills

• Experience leading engineers to tackle a large-scale AI problem
• Strong technical background & Strategic thinking
• Experience in Machine Learning, Big Data and Deep Learning
• Experience in GAI and/or LLMs

You will Benefit from our Culture

• 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 $175,000-$287,000.

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.