Staff AI Engineer
$175k - $287k Company Description LinkedIn 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. Job Description 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
Fill out an Accommodation request here: 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:
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. San Francisco Fair Chance Ordinance Pursuant to the San Francisco Fair Chance Ordinance, LinkedIn will consider for employment qualified applicants with arrest and conviction records. Pay Transparency Policy Statement As a federal contractor, LinkedIn follows the Pay Transparency and non-discrimination provisions described at this link: 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:
- 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.
- 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 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.
- 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
Fill out an Accommodation request here: 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. San Francisco Fair Chance Ordinance Pursuant to the San Francisco Fair Chance Ordinance, LinkedIn will consider for employment qualified applicants with arrest and conviction records. Pay Transparency Policy Statement As a federal contractor, LinkedIn follows the Pay Transparency and non-discrimination provisions described at this link: 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:
Vacancy posted 2 days ago
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