Staff AI Engineer

Job Description

Linked In is the worlds largest professional network, built to create economic opportunity for every member of the global workforce. Our products help people make powerful connections, discover exciting opportunities, build necessary skills, and gain valuable insights every day. Were also committed to providing transformational opportunities for our own employees by investing in their growth. We aspire to create a culture thats built on trust, care, inclusion, and fun where everyone can succeed.

This role will be based in Sunnyvale, San Francisco, or New York City. At Linked In, 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 Linked In office on select days, as determined by the business needs of the team.

AI is at the core of how Linked In 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 Linked In scale. You won't just train models, you will own the recommender and classification system that power Linked In’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.

• 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.

You’ll work on AI systems with immediate, measurable impact on more than a billion members, alongside engineers who set the industry bar for recommendation systems at scale powered by the latest open source generative models and GPU inference. We encourage staying up to date on industry state-of-the-art and sharing your work with the community through conference, journal, and blog publications. We invest in your growth with real mentorship, we trust you with real ownership, and we measure what matters: impact, not output according to our core engineering principles.

• Impact: quantify the value you created for members, the business and your team
• Leadership
  : communicate and lead through influence, not authority
• Execution: deliver impact with a sense of urgency
• Craft: innovate and create leverage with high-quality solutions

• 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

• 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…