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Senior Staff AI Engineer | Senior Technical Lead - AI Modeling

$241k - $326k
Full-time

Linkedin

Company Description

LinkedIn is the world’s 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. We’re also committed to providing transformational opportunities for our own employees by investing in their growth. We aspire to create a culture that’s built on trust, care, inclusion, and fun – where everyone can succeed.

Join us to transform the way the world works.

 

Job Description

Location: 

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.

This role will be based in Sunnyvale, CA.

Overview:

This role is a Senior Technical Leader (Uber TL, L7) with scope over a team of 15-25 engineers. Solutions will vary and can encompass GAI, Reinforcement Learning, Deep Learning, modern recommendations / relevance systems and algorithms, and much more - often with LLMs and multi-modal framework as an underpinning. Work can span many domains such as Search, Ads, Notifications, Feed, and Agentic solutions. 

Advanced modeling skills are required, and the work will include expert hands-on contribution in addition to thought and technical leadership. 

Responsibilities:

  • This is a Senior Technical Leader role that will provide thought leadership and expert individual contribution for a team of Senior and Staff/Lead AI Engineers, reporting to a Director of AI Engineering.
  • Lead the development of next-generation recommender systems on top of foundational LLMs.
  • Design and train large language models (LLMs) from scratch or adapt existing models to achieve state-of-the-art performance on recommendation tasks.
  • Drive architectural decisions for foundational model development and deployment, ensuring scalability, efficiency, and robustness.
  • Provide technical leadership and mentorship to a team of engineers, fostering a culture of innovation and excellence.
  • Collaborate with cross-functional teams (product engineering, infrastructure) to identify high-impact opportunities and integrate models into new use cases across the LinkedIn ecosystem. 
  • Define and execute rigorous evaluation strategies to benchmark the performance of foundational models against state-of-the-art solutions.

Qualifications

Basic Qualifications:

  • 2+ years as a Technical Lead, Staff Engineer, Principal Engineer, or equivalent.

  • 5+ years of industry experience in AI or Machine Learning Engineering.

  • BA/BS Degree in Computer Science or related technical discipline or equivalent practical experience

Preferred Qualifications:

  • 10+ years of overall industry (or industry + research) experience in AI and/or Machine Learning, including significant work with end-to-end solutions.

  • PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related field Expert-level understanding of deep learning architectures, particularly Transformer models, and experience training and fine-tuning LLMs and applying them to recommender systems.

  • Also, extensive experience developing models with advanced reasoning and planning capabilities.

  • Strong programming skills in Python and relevant deep learning frameworks (e.g., PyTorch).

  • Significant contributions to the field of AI, demonstrated through publications in top-tier conferences (e.g., NeurIPS, ICLR, ICML, ACL) or impactful open-source projects.

  • Proven ability to build models that accurately interpret and follow complex, nuanced instructions (zero-shot or few-shot). Also, experience developing models that can evaluate their own progress, identify errors, and adjust their approach accordingly.

  • Strong understanding of reinforcement learning (RL) techniques and their application to agent training in language-based environments.

  • Experience with specific techniques for improving reasoning and planning in LLMs: e.g., program synthesis, symbolic reasoning, neuro-symbolic AI.

Suggested Skills:

  • AI Modeling

  • Technical Leadership

  • Large Language Models (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.

Compensation:

LinkedIn is committed to fair and equitable compensation practices. The pay range for this role is $241,000 - $326,000. Actual compensation packages are based on a wide array of factors unique to each candidate, including but not limited to skill set, years & depth of experience, certifications and specific office location. This may differ in other locations due to cost of labor considerations.

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

Additional Information

Equal Opportunity Statement 

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:

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 for Job Candidates ​

Please follow this link to access the document that provides transparency around the way in which LinkedIn handles personal data of employees and job applicants:

Vacancy posted 8 hours ago
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