Senior Systems Software Engineer, TAO Machine Learning Data Modeling

Nvidia • Santa Clara, CA

73d • $148,000 - $287,500

About The Position

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.

Requirements

• 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.

Nice To Haves

• 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.

Responsibilities

• 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.

Benefits

• Equity and benefits.

What This Job Offers

• Career Level: Senior
• Industry: Computer and Electronic Product Manufacturing
• Education Level: Bachelor's degree
• Number of Employees: 5,001-10,000 employees