Senior Machine Learning Performance Engineer - AI for Science at Scale

Key Skills

Aartificial intelligence, CUDA kernels, Framework, JAX framework, Machine learning techniques, MLflow, NVIDIA Jetson, PyTorch, TensorFlow

Job Description

NVIDIA has become the platform upon which every new AI-powered application is built. We are seeking a Senior Machine Learning Performance Engineer to join our team of scientists and engineers passionate about building the next generation of scientific machine learning (ML) frameworks. Starting with digital biology, we will enable powerful and efficient ML methods through collaborations with industry and academic partners. Together, we will advance NVIDIA’s capacity to accelerate AI for Science and industries that depend on it.

What you'll be doing:

• Design performance and accuracy evaluation frameworks and carry out evaluations of pioneering ML models used in scientific discovery. Identify bottlenecks, design and implement solutions at scale such as pipeline or tensor parallelism.

• Drive the testing and maintenance of the algorithms and software stack used in the AI for Science applications within the company and in the open source community

• Stay up-to-date on the latest machine learning technologies and evaluate their potential as solutions to accuracy and/or computational performance bottlenecks.

• Collaborate with multiple high performance computing, AI infrastructure, and research teams

• Contribute to documentation or educational content relating to product

What we need to see:

• Advanced degree in a quantitative field such as Computer Science, Computational Biophysics, Computational Chemistry, Physics, Mathematics, or equivalent experience

• 8+ years of relevant experience

• Consistent track record of performance engineering in large scale AI model training and inference applications, and deep understanding of paradigms of parallelism in these applications such as tensor or pipeline parallelism.

• Expertise in modern machine learning frameworks such as PyTorch, TensorFlow, JAX, Warp and distributed learning strategies within them

• Up-to-date knowledge of ML research in scientific discovery

• Experience with software design, building, packaging and launching software products based on ML research

• Recognized for technical leadership contributions, capable of self-direction, and ability to learn from and teach others

• You should display strong communication skills, be organized and self-motivated, and play well with others (be an excellent teammate!)

Ways to stand out from the crowd:

• Experience with CUDA programming or familiarity with CUDA extensions of ML frameworks

• Contributor to major scientific ML codebase

With highly competitive salaries and a comprehensive benefits package, Nvidia is widely considered to be one of the technology industry's most desirable employers. We have some of the most forward-thinking, resourceful and dedicated people in the world working with us and our engineering teams are growing fast in some of the hottest innovative fields: Quantum Computing, Artificial Intelligence, and Autonomous Vehicles. Are you a creative and autonomous engineer with a real passion for machine learning, computational chemistry, data science & parallel computing? If so, we want to hear from you.

The base salary range is 180,000 USD - 345,000 USD. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.

You will also be eligible for equity and benefits. NVIDIA accepts applications on an ongoing basis.

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.