NVIDIA is hiring a Senior Systems Software Engineer for machine learning data modeling to join the TAO Toolkit ML Data and Platforms Team. Our team builds frameworks, services, algorithms, and tools that power the largest NVIDIA Multi-Modal Foundation Models and their customization. In this role, you will develop novel algorithms to make automated sense of petabytes of unstructured data using machine and deep learning algorithms, in collaboration with multiple deep learning architects and engineers to enable the development of pioneering AI models.
What you’ll be doing:
Help in finding and creating (synthetic generation using GenAI/Simulation) the right data for a Multi-Modal model with scalable systems.
Design various (ML and DL) architectures and loss functions to ingeniously formulate automated pseudo-labeling and GenAI for various multi-modal tasks.
Design and develop an active (and passive) learning paradigm within (and out) of the loop annotators to iteratively mine informative data.
Design insightful metrics (in settings: unsupervised, semi-and-supervised) for performance characterization of various models and data.
Build scalable and robust ETL pipelines using novel and meaningful ML and DL models to deliver high-quality datasets.
Work with internal teams to define requirements, enhance products, and automate workflows.
What we need to see:
Bachelor's degree in Computer Engineering, Computer Science, Electrical Engineering, Robotics, or related field (or equivalent experience).
5+ years of ML / DL-related engineering experience with strong architecture and design skills.
Excellent background and understanding of the deep roots of ML and DL.
Proficient in understanding of perception systems, 2D or 3D and/or Temporal.
Expertise with an understanding of out-of-distribution and related concepts.
Knowledge of PyTorch, distributed machine learning, and distributed file systems.
5+ years leading complex sometimes ambiguous projects, particularly in high-throughput services at supercomputing scale.
Ways to stand out from the crowd:
Good familiarity with multiple perception domains - Object detection, Segmentation, Multiple Object Tracking, Metric Learning.
Knowledge of internal workings of Diffusion models.
Familiarity with 3D geometrical aspects of Simulation and Inverse Computer Graphics.
Proficient in running applications on cloud platforms using Kubernetes and Docker, and ML frameworks like Pytorch.
Proficient in building systems and familiar with deep learning architectures and tools like NVIDIA TensorRT-LLM, Multimodal-LLM, and Triton Server.
NVIDIA is widely considered to be one of the technology industry's most desirable employers. We have some of the most forward-thinking and hard-working people working with us and our engineering teams. If you're a creative engineer with a real passion for building scalable and robust infrastructure, we want to hear from you.
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 148,000 USD - 235,750 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4.You will also be eligible for equity and benefits.
Top Skills
What We Do
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 AI — 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, NVIDIA is increasingly known as “the AI computing company.”
