Senior AI Engineer, VideoAI

LinkedIn


Job Location:

Mountain View, CA - USA

Monthly Salary: Not Disclosed
Posted on: 5 hours ago
Vacancies: 1 Vacancy

Department:

Engineering

Job Summary

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

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. 

The Video AI team sits at the heart of our LinkedIns ambitious growth strategy. Our team is a dynamic group of machine learning experts dedicated to revolutionizing the way we interact with video content. This team is at the forefront of developing cutting-edge artificial intelligence technologies that enhance video understanding search and personalization. By leveraging state-of-the-art AI techniques the Video AI team is poised to open up new ways of engaging with videos on LinkedIn.

Our work encompasses a range of applications from real-time video analytics to intelligent content recommendation systems positioning our company as a leader in the rapidly evolving landscape of video technology. As LinkedIn continues to revolutionize our market presence the Video AI teams expertise will be instrumental in shaping our product offerings and achieving our strategic goals ensuring we stay ahead of the competition and deliver unparalleled value to our 1 billion global users.

Below are a few examples of the problem spaces we work in (and much more!):

  • Video Understanding: Building state of the art content understanding models and content embeddings to power all video use cases.

  • Video Feed Personalization: Identifying the most engaging content and distributing to users.

  • Video Search: Tackling the multimodal search problem delivering videos that provide the highest user value.

  • Video Safety: Safeguarding users from malicious actors and content building an open and safe community for all.

Responsibilities

The Video AI team is at the forefront of building the AI systems that power LinkedIns next generation of video experiences for more than one billion members. As a Senior AI Software Engineer you will own end-to-end machine learning systems that run in production at LinkedIn scale from multimodal video understanding and large-scale recommendation to retrieval ranking and search. You wont just train models; youll own the production AI systems that connect members with relevant engaging and trustworthy video content. Your responsibilities span the entire product lifecycle from translating product requirements into scalable ML architectures developing and deploying state-of-the-art models designing and evaluating online experiments to optimizing the distributed GPU infrastructure that serves billions of recommendations in milliseconds.


Qualifications :

Basic Qualifications:

  • BA/BS Degree in Computer Science Machine Learning or related technical discipline or related practical experience.

  • 2 years experience in software design development and algorithm related solutions.

  • 2 years experience in programming languages such as Java Python etc.

  • 2 years experience with machine learning data mining and information retrieval or natural language processing

Preferred Qualifications:

  • 4 years of relevant AI/Machine Learning experience.

  • MS or PhD in Computer Science or related technical discipline

  • 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 in Machine Learning and Deep Learning

  • Experience in Big Data

  • Strong technical background & Strategic thinking

  • 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 $144000 - $236000.  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 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: 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 LinkedIns 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: 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: Work :

No


Employment Type :

Full-time

This role will be based in New York or San Francisco.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 Lin...

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