
Senior Software Engineer, AV Analysis Platform
Required skills
- AV log data analysis
- model behavior assessment
- regression debugging
- critical metrics and insights
- evaluator execution
- performance tuning
- structured outputs
- output schema evolution
- observability
- production readiness
Nice to have
- self-driving car development
- simulation
- evaluation
- analysis workflows
- performance profiling
- resource usage analysis
Role summary
NVIDIA is seeking a senior software engineer for their Autonomous Vehicle (AV) Analysis Platform team. This role focuses on building and scaling infrastructure for AV development, involving distributed systems, data platforms, and developer efficiency. Responsibilities include designing and enhancing systems for log data analysis, model behavior assessment, regression debugging, and metric production at scale. The engineer will improve analyzer workflows, build reliable services and APIs, define data contracts, and enhance system stability, performance, and observability. The position requires strong programming skills in Python or Go, experience with distributed systems, API design, data pipelines, schema evolution, and production readiness. A BS/MS in a related field or equivalent experience is needed, with a minimum of 12 years of software engineering experience. The role is hybrid with a salary range of $224,000 - $356,500 USD.
NVIDIA is seeking a senior software engineer to help build and scale evaluation and analysis infrastructure for Autonomous Vehicle development. This role sits at the intersection of AV tooling, distributed systems, data platforms, and developer efficiency. You will develop and enhance systems that allow AV engineers to run AV log data analysis, assess model behavior, debug regressions, and produce critical metrics and insights at scale.
This engineer should be able to operate independently, partner deeply with senior technical leads, and bring clarity to complex platform decisions spanning evaluator execution at high-scale, performance tunings, structured outputs and output schema evolution, observability, and production readiness. This role directly improves how AV engineers examine autonomous driving performance, analyze regressions, validate analyzers, and trust the results produced by NVIDIA’s AV infrastructure. The ideal candidate will help make evaluation workflows faster, safer, more observable, and easier for teams to adopt.
What you'll be doing:
- Design and build evaluation and analysis tooling used by AV and ML engineers.
- Improve analyzer workflows, including onboarding, execution, qualification, and production observability.
- Build reliable services, APIs, CI pipelines, and UI-facing workflows across the stack.
- Define and evolve data contracts for analyzer outputs, including structured schemas, tabular data, time-series data, and metadata.
- Improve system stability, performance, traceability, alerting, and operational debuggability for high-scale workloads.
- Partner with AV engineering, data platform, infrastructure, and product teams to deliver end-to-end user workflows.
- Establish guardrails for analyzer rollout, including pre-merge validation, output-size controls, runtime/memory metrics, and production monitoring.
What we need to see:
- BS/MS in Computer Science, Computer Engineering, Electrical Engineering, or a related field, or equivalent experience.
- 12+ years of software engineering experience building production systems, developer tools, data platforms, or evaluation infrastructure.
- Strong programming skills in Python, Go, or similar languages.
- Experience designing distributed systems, workflow orchestration, APIs, backend services, or data pipelines.
- Ability to reason across systems software, data schemas, backend services, and user-facing tooling.
- Experience collaborating across teams and driving ambiguous technical work to completion.
- Ability to balance new feature development with production stability, maintainability, and user support, while demonstrating agility and adaptability in a fast paced environment.
- Experience with Protobuf, Parquet, schema evolution, data contracts, and large-scale analytical storage.
Ways to stand out from the crowd:
- Background with self-driving car development, simulation, evaluation, or analysis workflows.
- Experience with observability, performance profiling, resource usage analysis, and production reliability.
- Experience improving legacy systems through incremental migration, deprecation, and architecture cleanup.
#LI_Hybrid
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.You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until October 26, 2026.This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive 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.Originally posted on Himalayas
Sample NVIDIA interview questions
- 1
Design a system for a rock paper scissors game
system designmedium - 2
Implement a distributed data migration management platform.
system designmedium - 3
Design a Distributed Build System with Cross-Data Center Artifact Sharing
system designhard - 4
Design a distributed training system for a trillion-parameter language model
system designmedium - 5
Develop a distributed tracing system for tracking and debugging.
system designmedium
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