Staff Specialist AI Engineer - Foundations

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..

Job Description

As a Staff AI Scientist, you will play a pivotal role in advancing LinkedIn's efforts in cutting-edge AI research and development, focusing on large-scale foundation models and AI innovations. You will specialize in developing, training, and optimizing foundation models, including Large Language Models (LLMs), utilizing state-of-the-art deep learning architectures such as multi-billion parameter transformers and scaling them to serve LinkedIn's global user base. Your work will involve the design and deployment of high-performance AI systems, leveraging GPUs and other hardware accelerators for large-scale training and inference.

You will collaborate with a world-class team of researchers and engineers to develop and advance the next generation of AI models to push the boundaries of AI at scale, working on complex problems such as distributed training, model parallelism, and system co-design. A successful candidate will be comfortable operating at the intersection of AI research and engineering, with a deep understanding of the latest advancements including but not limited to large model training, post-training techniques for planning and reasoning, fine-tuning strategies, reinforcement learning techniques.

Responsibilities

• Lead and contribute to the research, design, and development of large-scale foundation AI models, focusing on LLMs, transformer architectures, and cutting-edge AI systems.
• Publish findings and innovations in leading academic and industry forums, including top-tier AI conferences such as ICML, NeurIPS, ICLR, ACL, as well as through patents and other relevant venues.
• Stay abreast of the latest academic and industry research, applying relevant findings to improve LinkedIn's AI capabilities.
• Innovate in large-scale model training, leveraging GPUs and specialized hardware for optimal performance.
• Develop and maintain scalable AI pipelines, optimizing training and inference workflows to handle vast amounts of data.
• Mentor junior engineers and contribute to team growth and knowledge sharing.
• Collaborate with cross-functional teams of machine learning engineers, infrastructure engineers, and AI researchers to deliver impactful AI innovations across LinkedIn's products.

Basic Qualifications

• Bachelor's degree in Computer Science or related technical field or equivalent practical experience
• 4+ years of experience with programming languages such as Java, Python, etc.
• 4+ years of experience in machine learning or AI engineering.
• 4+ years of experience in the design and development of algorithmic solutions.

Preferred Qualifications

• 6+ years of hands-on experience in large-scale model training, model-system co-design, or large AI systems.
• PhD in Computer Science or a relevant field, or a Bachelor's degree with 6+ years of industry experience in AI/ML.
• Proven research and innovation track record through publications in top-tier conferences (e.g., NeurIPS, ICML) and/or patents.
• Experience leading research projects and collaborating across teams to drive research into tangible impact.
• Proven experience in building and optimizing large-scale AI/ML models using frameworks such as PyTorch, PySpark, and CUDA.
• Expertise in distributed training, model parallelism, and hardware acceleration for AI workloads, including GPUs and TPUs.
• Demonstrated ability to solve complex AI challenges in large-scale environments, optimizing models for efficiency and scalability.
• Strong proficiency in AI system design, model optimization, and the development of production-quality AI pipelines.
• Published work in AI research or significant contributions to industry-leading AI technologies.
• Excellent communication skills and a demonstrated sense of ownership over key AI projects.

Suggested Skills

• Large Language Models (LLM)
• Generative AI (GAI)
• AI Research and Development
• GPU and Hardware Acceleration
• Distributed AI Systems and Model Parallelism

- 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 $170,000 - $277,000. Actual compensation packages are based on several factors 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 an annual performance bonus, stock, benefits, and/or other applicable incentive compensation plans. For more information, visit LinkedIn 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.

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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.

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