Engineering Jobs in Mountain View, CA (Now Hiring) — 895 open — Page 44

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.

Team Overview:

The Notification AI team builds large-scale, high-quality machine learning systems that deliver the right content to the right member, through the right channel, at the right time—and at the right frequency. Our mission is to maintain a healthy, relevant, and delightful notification ecosystem that helps members achieve their professional goals while ensuring every interaction provides meaningful value.

We power AI-driven systems that target, rank, and make decisions across LinkedIn’s notification portfolio, enabling product teams to deliver member value efficiently and responsibly. Notifications AI directly shapes the value members get from the platform, driving over 50% of total engagement on LinkedIn and helping millions of professionals reconnect with opportunities that matter.

Our work spans large language models, recommendation systems, and scalable architectures that deepen LinkedIn’s understanding of members—their skills, journeys, and evolving intent—so we can surface the most relevant content, jobs, and connections to help them grow their professional networks meaningfully.

The team has an ambitious roadmap and partners closely with Product, Engineering, and Data Science to deliver scalable, leverageable AI solutions with global member impact. If you’re looking to lead a highly visible, fast-moving, and exceptionally talented team at the intersection of cutting-edge research and real-world impact—and have fun while doing it—Notifications AI is the place for you!

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 job is based in Sunnyvale, CA. 

Key Responsibilities:

Lead a team of AI Scientists/Engineers to build scalable notification recommendation systems at Linkedin. We’re looking for a technical manager with strong leadership, technical vision, and collaboration skills to drive impact and build great team culture.

Lead and inspire the team:
Manage and grow a high-performing team of researchers/applied scientists, and engineers. Attract, mentor, and develop diverse talent while fostering an inclusive, collaborative environment where people feel empowered to share ideas, take smart risks, and grow into technical leaders.

Set strategy and direction:
Translate product and business needs into a clear, focused technical roadmap. Ensure the team’s day-to-day work aligns with LinkedIn’s mission and long-term priorities. Partner with senior leadership to shape long-range AI and infrastructure strategy.

Advance state-of-the-art recommender systems:

Lead the team in developing and deploying scalable retrieval and ranking systems powered by large language models (LLMs) and advanced ML solutions to optimize notification timing and delivery decisions. Leverage LinkedIn’s rich data ecosystem to ground model outputs, improve relevance, and strengthen end-to-end notification quality. As a hands-on technical manager, guide critical technical decisions and collaborate closely with technical leaders across the organization.

Ensure scalability and efficiency:

Collaborate with infrastructure and platform teams retrieval and serving system performance optimizations through advanced techniques like GPU-powered retrieval-as-ranking optimization, adaptive caching, and parameter-efficient fine-tuning. Maintain high standards for reliability, scalability, and latency.

Drive alignment and cross-functional collaboration:
Work closely with partner teams to identify shared opportunities, align on long-term goals, and maintain consistent progress. Address misalignments proactively with clarity, empathy, and data-driven reasoning.

Promote innovation and high-quality execution:
Create a culture that encourages experimentation, curiosity, and continuous improvement. Ensure the team adheres to strong engineering and scientific practices, enabling rapid iteration through A/B testing and rigorous evaluation.

Basic Qualifications:

• BA/BS in Computer Science or other technical discipline, or related practical technical experience
• 1+ year(s) of management experience or 1+ year(s) of staff level engineering experience with management training
• 5+ years of related industry experience in software design, development, and algorithm related solutions
• 1+ years of experience in software engineering/technical engineering management and people management
• 1+ year(s) of management experience or 1+ year(s) of staff level engineering experience with management training
• Hands on experience in data modeling and machine learning

Preferred Qualifications:

• Master’s degree in Computer Science, Information Retrieval, Machine Learning, Natural Language Processing, or a related field
• Ph.D. in Computer Science, Information Retrieval, Machine Learning, Natural Language Processing, or a related discipline
• Strong technical background and experience leading teams in Machine Learning, LLMs, Retrieval systems, Large-model optimization, On-device ML
• Experience designing and deploying large-scale recommender systems
• Published work in academic or industry forums
• 7+ years of industry experience

Suggested Skills:

• Large-scale AI problem
• Technical background 
• Strategic thinking
• Machine Learning, Big Data and Deep Learning
   

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.

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Compensation:

LinkedIn is committed to fair and equitable compensation practices. The pay range for this role is $170,000 to $277,000. 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. For more information, visit https://careers.linkedin.com/benefits. 

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.

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• Documents in alternate formats or read aloud to you
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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.

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Pursuant to the San Francisco Fair Chance Ordinance, LinkedIn will consider for employment qualified applicants with arrest and conviction records.

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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: https://www.linkedin.com/legal/candidate-portal.