Senior Software Engineer, Data Infrastructure for Robotics Research

Posted 17 Days Ago
2 Locations
In-Office or Remote
224K-426K
Senior level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
The role involves designing and maintaining data infrastructure for robotics, optimizing GPU utilization, and collaborating with researchers on advanced data technologies.
Summary Generated by Built In

We are seeking a Senior 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).

  • 12+ 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 224,000 USD - 356,500 USD for Level 5, and 272,000 USD - 425,500 USD for Level 6.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until October 3, 2025.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.

Top Skills

Spark
C++
Cuda
Jax
Kubernetes
Lancedb
Python
PyTorch
Ray
SQL
TensorFlow
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The Company
HQ: Santa Clara, CA
21,960 Employees
Year Founded: 1993

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.”

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