Senior Systems Software Engineer, TAO Machine Learning Data Modeling at NVIDIA

Santa Clara, California, United States

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Artificial Intelligence, TechnologyIndustries

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

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

Skills

Key technologies and capabilities for this role

PyTorchDistributed Machine LearningDistributed File SystemsDeep LearningMachine LearningPerception SystemsGenAIETL PipelinesActive LearningPseudo-Labeling

Questions & Answers

Common questions about this position

What is the base salary for this position?

This information is not specified in the job description.

Is this a remote position or does it require working in an office?

This information is not specified in the job description.

What are the required skills for this Senior Systems Software Engineer role?

Candidates need a Bachelor's degree in Computer Engineering, Computer Science, or related field, 5+ years of ML/DL engineering experience with strong architecture skills, proficiency in perception systems, expertise in out-of-distribution concepts, and knowledge of PyTorch, distributed ML, and distributed file systems.

What is the company culture like at NVIDIA for this team?

NVIDIA has forward-thinking and hard-working engineering teams, and they seek creative engineers passionate about building scalable and robust infrastructure.

What makes a candidate stand out for this role?

Stand out with familiarity in perception domains like object detection and segmentation, knowledge of Diffusion models, 3D simulation aspects, proficiency in cloud platforms with Kubernetes and Docker, and experience with tools like NVIDIA TensorRT-LLM and Triton Server.

NVIDIA

Designs GPUs and AI computing solutions

About NVIDIA

NVIDIA designs and manufactures graphics processing units (GPUs) and system on a chip units (SoCs) for various markets, including gaming, professional visualization, data centers, and automotive. Their products include GPUs tailored for gaming and professional use, as well as platforms for artificial intelligence (AI) and high-performance computing (HPC) that cater to developers, data scientists, and IT administrators. NVIDIA generates revenue through the sale of hardware, software solutions, and cloud-based services, such as NVIDIA CloudXR and NGC, which enhance experiences in AI, machine learning, and computer vision. What sets NVIDIA apart from competitors is its strong focus on research and development, allowing it to maintain a leadership position in a competitive market. The company's goal is to drive innovation and provide advanced solutions that meet the needs of a diverse clientele, including gamers, researchers, and enterprises.

Santa Clara, CaliforniaHeadquarters

1993Year Founded

$19.5MTotal Funding

IPOCompany Stage

Automotive & Transportation, Enterprise Software, AI & Machine Learning, GamingIndustries

10,001+Employees

Benefits

Company Equity

401(k) Company Match

Risks

Increased competition from AI startups like xAI could challenge NVIDIA's market position.

Serve Robotics' expansion may divert resources from NVIDIA's core GPU and AI businesses.

Integration of VinBrain may pose challenges and distract from NVIDIA's primary operations.

Differentiation

NVIDIA leads in AI and HPC solutions with cutting-edge GPU technology.

The company excels in diverse markets, including gaming, data centers, and autonomous vehicles.

NVIDIA's cloud services, like CloudXR, offer scalable solutions for AI and machine learning.

Upsides

Acquisition of VinBrain enhances NVIDIA's AI capabilities in the healthcare sector.

Investment in Nebius Group boosts NVIDIA's AI infrastructure and cloud platform offerings.

Serve Robotics' expansion, backed by NVIDIA, highlights growth in autonomous delivery services.

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