Staff Software Engineer, Machine Learning

LinkedIn • Mountain View, CA

17h • Hybrid

About The Position

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.

Requirements

• 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.

Nice To Haves

• 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.

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.

Benefits

• 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 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.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 1,001-5,000 employees