Principal Engineer - AV Simulation and Evaluation

NVIDIA•Santa Clara, CA

3d•$272,000 - $431,250

About The Position

NVIDIA is seeking a Principal Software Engineer to architect and build core platform systems that accelerate Physical AI development, including autonomous driving and robotics. This technical role focuses on the intersection of data architecture, distributed systems, and autonomous vehicle development across cloud, local, and on-road environments. The engineer will own deep technical areas end to end, including AV and robotics simulation infrastructure and AV performance evaluation. The role involves building simulation and evaluation infrastructure for AV and ML engineers developing Level 4 self-driving capabilities; evolving efficient, interoperable, and correct data formats; and building reliable services, APIs, data pipelines, and workflows that can operate at the scale of hundreds of millions of runs per day. The engineer will work closely with AI and Robotics teams, optimize system performance, develop diagnostic and observability tooling, and promote adoption of standards and technologies in the physical AI tooling ecosystem. The expected base salary range is USD 272,000–431,250. The employee will also be eligible for equity and benefits. Applications will be accepted at least until November 6, 2026. This posting is for an existing vacancy.

Requirements

BS or MS in Computer Science, or equivalent experience.
15+ years of professional software engineering experience focused on distributed systems and data-intensive applications.
Proficiency in Go, Python, or Java, and experience operating across the full backend stack.
Deep experience building high-performance, low-latency data systems, including binary serialization, efficient data encoding, and columnar data formats.
Strong understanding of distributed systems, including concurrency, consistency tradeoffs, latency optimization, and compute-efficient design.
Ability to identify and fix performance bottlenecks across the stack, including redesigning protocols and data models.
Experience designing and implementing workflows across distributed systems.
A record of building foundational systems that multiple teams depend on, with high reliability and scale.
Strong communication skills, including the ability to explain nuanced system designs to technical and non-technical partners and communicate with users in their language.
Ability to lead cross-functional projects, influence without authority, and deliver across organizational boundaries.

Nice To Haves

Experience building orchestration or workflow execution systems, such as Temporal.io or similar workflow engines.
Experience with sensor data pipelines and formats such as ROS, MCAP, AV logs, Parquet, or Apache Arrow.
Understanding of AV and robotics concepts such as kinematics, control systems, computer vision, motion planning, or neural networks.
Experience improving legacy systems through incremental migration, deprecation, and architecture cleanup.

Responsibilities

Design and build simulation and evaluation infrastructure for AV and ML engineers to accelerate development of Level 4 self-driving capabilities.
Evolve efficient AV evaluation data formats, designing for performance, interoperability, and correctness across formats such as Protobuf, Arrow, Parquet, and MCAP.
Collaborate with AI and Robotics teams to understand their simulation and evaluation needs.
Build reliable services, APIs, data pipelines, and AV simulation and evaluation workflows and frameworks that operate at the scale of hundreds of millions of runs per day.
Optimize performance through profiling, parallelization, memory efficiency, query optimization, and protocol redesign.
Build diagnostic and observability tooling that helps teams understand and debug data and test pipelines.
Drive adoption of new standards and technologies in the physical AI tooling ecosystem.
Lead cross-functional projects and influence work across organizational boundaries.