AI Insights
NVIDIA

Principal Software Engineer, Data Infrastructure for Robotics Research

NVIDIA · Santa Clara, California, US
full-timestaff (15-25 yrs)Posted 41d ago
Data Engineering / ML InfrastructureIC5IC + ManagementOn-site
StackPythonC++PyTorchJAXTensorFlowKubernetesRayApache SparkLanceDBSQLCUDAGPU programmingETL pipelinesMLOpsdistributed systemsdata infrastructuremultimodal dataobservability tooling

Summary

NVIDIA is hiring a Principal Software Engineer to build foundational data infrastructure for robotics research, closely supporting the GEAR group and Project GR00T — a moonshot initiative for humanoid robot foundation models. The role involves designing large-scale distributed ETL systems, optimizing GPU/cluster utilization, and developing multimodal data pipelines for massive robotics datasets.

About the role

We are seeking a Software Engineer to join a new team building the foundational infrastructure for Robotics Research. This new team will work very closely with NVIDIA’s Generalist Embodied Agent Research (GEAR) group. The near term focus is Project GR00T, NVIDIA’s moonshot initiative at building foundation models and full-stack technology for humanoid robots. This particular position will focus on data infrastructure.

You will work with an amazing and collaborative research team that consistently produces influential works on multimodal foundation models, large-scale robot learning, embodied AI, and physics simulation. Your contributions will have a significant impact on our research projects and product roadmaps.

What you’ll be doing:

  • Design and maintain large-scale distributed data ETL and data management systems to support multi-modal foundation models for robotics.

  • Optimize GPU and cluster utilization for efficient model training and fine-tuning on massive datasets.

  • Implement scalable data loaders and preprocessors tailored for multimodal datasets, including videos, text, and sensor data.

  • Develop robust observability tools and procedures for this data infrastructure to ensure reliability and performance.

  • Collaborate with researchers to integrate cutting-edge data technologies into scalable training and eval pipelines.

What we need to see:

  • Bachelor's degree in Computer Science, Robotics, Engineering, or a related field (or equivalent experience).

  • 15+ years of full-time industry experience in large-scale MLOps and AI infrastructure.

  • Experience with ML frameworks like PyTorch, JAX, or TensorFlow.

  • Experience with Kubernetes and Ray.

  • Deep understanding of data frameworks and standards like SQL, Apache Spark, LanceDB.

  • Experience of GPU acceleration and CUDA programming.

  • Strong programming skills in Python and a high-performance language such as C++ for efficient system development.

Ways to stand out from the crowd:

  • Master’s or PhD’s degree in Computer Science, Robotics, Engineering, or a related field;

  • Demonstrated Tech Lead experience, coordinating a team of engineers and driving projects from conception to deployment;

  • Strong experience at building and operating large-scale data infrastructure;

  • Strong experience and curiosity in frontier AI research

NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and productive people in the world. Please join us and be part of the forefront of developing general-purpose robots and large-scale foundation models!

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 272,000 USD - 431,250 USD for Level 6, and 320,000 USD - 488,750 USD for Level 7.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until March 10, 2026.

This posting is for an existing vacancy. 

NVIDIA uses AI tools in its recruiting processes.

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.

What you'll do

1Design and maintain large-scale distributed data ETL and data management systems for multimodal robotics foundation models
2Optimize GPU and cluster utilization for efficient model training and fine-tuning on massive datasets
3Implement scalable data loaders and preprocessors for multimodal datasets including video, text, and sensor data
4Develop robust observability tools and procedures to ensure reliability and performance of data infrastructure
5Collaborate with researchers to integrate cutting-edge data technologies into scalable training and evaluation pipelines

Requirements

15+ years of industry experience in large-scale MLOps and AI infrastructure engineering
Strong proficiency in Python and a high-performance language (C++) for systems development
Hands-on experience with ML frameworks (PyTorch, JAX, or TensorFlow) and cluster orchestration tools (Kubernetes, Ray)
Deep expertise with data frameworks and standards including SQL, Apache Spark, and LanceDB
Experience with GPU acceleration and CUDA programming for efficient model training workloads

Nice to have

Master's degree or PhD in Computer Science, Robotics, or Engineering
Tech Lead or engineering coordination experience
Large-scale data infrastructure design and operations
Frontier AI research experience or strong curiosity in the space

Role overview

Role family
Data Engineering / ML Infrastructure
Level
IC5 — ml_ai
Experience
15–25 years
Type
Hybrid (IC + Management)
Remote policy
On-site
Visa sponsorship
Not offered

Tech stack analysis

LANGUAGES
PythonC++
FRAMEWORKS
PyTorchJAXTensorFlowApache SparkRay
DATABASES
LanceDBSQL
INFRASTRUCTURE
KubernetesCUDAGPU clusters
TOOLS
ETL pipelinesobservability toolingdistributed data management systems

Green flags

5 items
Salary range explicitly disclosed ($272K–$488.75K base), plus equity — exceptional transparency for a tech role at this levelcompensation

Discover all 5 green flags for this role

Sign up free →

Benefits breakdown

See all benefits organized by category — health, financial, time off & more

Sign up free →

Hiring insights

JD quality
8/10
Urgency
medium
Autonomy
high
Team size
small (2-5)

See JD quality score, hiring urgency & team details

Sign up free →

Red flags

PRO4 items
15+ years of experience required for what is titled 'Software Engineer' (not Principal or Staff) — title may underrepresent seniority, could indicate title compression or leveling inconsistencyrequirements

See all 4 red flags — what the JD isn't telling you

Sign up free →

Interview insights

PRO

Get full interview breakdown — rounds, likely topics & prep tips

Sign up free →

Career path

PRO
Next roles
Distinguished Engineer, ML InfrastructureEngineering Director, AI PlatformVP of Engineering, Robotics

See where this role leads — full career progression

Sign up free →
About the company

NVIDIA is the world's leading designer of GPUs and AI computing platforms. Its chips power everything from gaming and data centers to autonomous vehicles and scientific research. With a market cap exceeding $2 trillion, NVIDIA's CUDA platform and AI accelerators have become the backbone of the global AI revolution.

HQSanta Clara, CA, USA
Build vs Maintainbuild
Cross-functionalYes