Senior Scientific Machine Learning Engineer...

NVIDIA Ltd.
Santa Clara, CA, United States
about 1 month ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Compensation
$152,000.0 - $241,500.0
Working hours
Regular working hours
Job source

Tech stack

Artificial Intelligence Nvidia CUDA Data Stores Python (Programming Language) Machine Learning Node.Js Performance Tuning Tensorflow Scientific Computating Software Engineering Reinforcement Learning Pytorch
+3 more
Deep Learning Parallel Computation Information Technology

Requirements

  • BS or MS degree (PhD preferred) in computer science, mathematics, computational science/engineering, or related technical field or equivalent experience

  • 5+ yrs of relevant experience

  • Strong Python programming skills

  • Familiarity with containers, numeric libraries, modular software design

  • Deep knowledge of state-of-the-art DNN architectures and machine learning techniques and algorithms (graph networks, diffusion models, reinforcement learning etc.) with experience in developing or using major deep learning frameworks (PyTorch, Tensorflow, JAX etc.)

  • Experience with development and application of machine learning techniques to solve real world scenarios in weather/climate

  • Experience with scientific visualization. Strong analytical skills with bias for action

  • Good time-management and organization skills to thrive in a fast paced, dynamic environment

  • Solid written and oral communications skills. Good teamwork and interpersonal skills

Ways to stand out from the crowd:

  • Experience using multi-node systems with data-parallel and model-parallel programming, performance optimization. Experience with HPC programming models (OpenMPI, NCCL), and/or CUDA or GPU kernel programming

  • Experience with nonlinear simulation tools and techniques, usage of major simulation codes. Published papers in the field of AI in scientific computing, especially in weather & climate applications

  • Familiarity with common tooling in the Earth-2 ecosystem (xarray, zarr, regridding, weather & climate data stores, etc.)

Benefits & conditions

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4.

About the company

NVIDIA (Santa Clara, CA)

NVIDIA’s deep learning and HPC platforms have made a huge impact in various fields and are broadly used across leading academic institutions, start-ups, and industry, including the world’s largest Internet companies. We need passionate and creative people to help us build the AI frameworks underlying the NVIDIA Earth-2 platform: a comprehensive family of open models, libraries, and frameworks that democratize global access to professional-grade weather and climate AI.

What you’ll be doing:

  • Work with some of the brightest minds in a premier AI company to develop leading machine learning frameworks, NVIDIA PhysicsNeMo and NVIDIA Earth2Studio, for our academic and industrial partners to build scientific ML technology and workflows for weather, climate, and earth system modeling.

  • Work with internal project teams to validate applications built using the framework on NVIDIA’s products, and integrate new functionalities from internal or external projects into the platform

  • Stay up to date with the latest research and innovations in deep learning techniques, implement and experiment with new ideas to develop and enhance NVIDIA’s Earth-2 technologies, with a focus on weather & climate AI, NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people on the planet working for us. If you’re creative and autonomous, we want to hear from you! NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern deep learning - the next era of computing - with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, we are increasingly known as “the AI computing company.” We’re looking to grow our company and establish teams with the most thoughtful people in the world.

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