Manager, ML Engineering

NVIDIA is hiring an engineering manager to lead and coordinate our efforts on Accelerated Machine Learning tools and Analytics Pipelines on GPUs within the RAPIDS group.  We’re expanding the team focused on building and optimizing how classical ML, gradient boosted trees, vector search and clustering models, etc. can achieve speed-of-light performance on single and multiple GPUs. 

This is a great opportunity to lead the team building for the next generation of machine learning and vector search.  In this role, you will use your leadership skills, design abilities, software engineering abilities, creativity, and community engagements to develop and extend current and future accelerated ML efforts.

What you'll be doing:

• Lead, mentor, and grow your engineering team and be responsible for the planning and execution of project as well as the quality, performance, and success of our ML libraries

• Work closely with Product, Project Management teams and external partners to work on ML applications, ensuring what we build benefits Machine Learning on GPUs for community as well as enterprise partners. 

• Define success and evaluation criteria, including reproducible workflows and datasets for library development, integration, and benchmarking.

• Provide technical leadership and mentorship to engineers that contribute across different teams and projects.

What we need to see:

• Master's or PhD degree, Computer Engineering/Science, or equivalent experience in Computer Science, Computer Systems, Engineering, or other related fields

• 8+ years of experience in Computer Science, Artificial Intelligence, Applied Math, or related field

• 3+ years of experience recruiting, training, and leading software engineering teams

• Strong written communication, collaboration, and presentation skills

• Experience with the full ML lifecycle, research->training->tuning->model deployment

• Strong analytical problem-solving skills, algorithms, and mathematics fundamentals

• Experience with distributed System development and deployment

• Experience in designing, developing, benchmarking, tuning, complex multi-language software stacks (C++/CUDA and Python)

• Experience working closely with Partners and Customers to build successful ML-based tooling

Ways to stand out from the crowd:

• Collaborated with partners and clients to develop effective machine learning tools.

• Proficient in vector search techniques and database management.

• Contributed to and maintained various open-source software initiatives. -

• Developed distributed algorithms for high-performance computing and cloud environments.

• Familiar with PyData libraries such as NumPy, Pandas, and Scikit-Learn; GPU programming experience is a bonus, but training is available.

NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking people in the world working for us. If you're creative and autonomous, we want to hear from you. NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High-Performance Computing,, and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services. Our work opens up new universes to explore, enables amazing creativity and discovery, and powers what were once science fiction inventions from artificial intelligence to autonomous cars. NVIDIA is looking for great people like you to help us accelerate the next wave of accelerated computing.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 224,000 USD - 356,500 USD for Level 3, and 272,000 USD - 425,500 USD for Level 4.Applications for this job will be accepted at least until November 4, 2025.NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.