We are seeking a Principal Software Engineer to architect and build core platform systems for the TestStudio team to accelerate Physical AI development, such as for Autonomous Driving & Robotics. This is a deeply technical role for someone with expertise at the intersection of distributed systems, data visualization, and Robotics across cloud, local, and on-road environments. You will own deep technical areas end-to-end: such as efficient binary data pipelines, streaming APIs to visualization backends, AI model validation and simulation infrastructure.
What you will be doing:
Design and implement high-performance data services for streaming, indexing, and querying sensor data at scale — across time-series, multi-modal, replay, and live sources.
Own and evolve the serialization and format layer: designing for performance, interoperability, and correctness across formats like Protobuf, Arrow, Parquet, and MCAP.
Collaborate with AI and Robotics teams to deeply understand their data access and evaluation patterns, then build platform APIs and tooling that measurably accelerate their work.
Optimize performance at every level: profiling, parallelization, memory efficiency, query optimization, and protocol redesign.
Build diagnostic and observability tooling that lets teams understand and debug their data and test pipelines.
Establish standard software development practices (code quality, testing, tracing, CI/CD) across data and orchestration services.
Actively drive the adoption of new standards and technologies in the physical AI tooling ecosystem.
What we need to see:
BS or MS in Computer Science or relevant field (or equivalent experience).
15+ years of professional experience in software engineering with a strong focus on distributed backend systems and data-intensive applications.
Deep proficiency in Go, Python, or Java — and experience operating across the full backend stack.
Deep experience building high-performance low-latency data systems: streaming pipelines, binary serialization, efficient data encoding, or columnar data formats.
Strong understanding of distributed systems: concurrency, consistency tradeoffs, latency optimization, and resource-efficient design.
Ability to identify and fix performance bottlenecks — through optimization across the stack, including protocol redesign.
Experience designing and implementing internal platform APIs used broadly across engineering organizations.
Track record of building foundational systems that teams depend on — with the engineering quality to match.
Ability to work with multi-functional teams, principals, and architects across organizational boundaries and geographies.
Excellent communication: able to translate nuanced system design to both technical and non-technical partners.
Ways to stand out from the crowd:
Understanding of AV & Robotics concepts such as kinematics, control systems, computer vision, motion planning, and/or neural networks.
Experience working with sensor data pipelines: ROS, MCAP, AV logs, Parquet, or similar domain formats.
Experience with real-time and replay streaming architectures (gRPC, WebSocket).
Experience building data visualization or data browser tooling for ML/AI teams.
Frontend experience (TypeScript, React) for building internal data tooling UIs.
You will also be eligible for equity and benefits.
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.Top Skills
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