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Salary: USD 160,000 - 180,000 / annual
May Mobility is transforming cities through autonomous vehicle technology, developing and deploying AVs powered by innovative Multi-Policy Decision Making (MPDM) technology. The company has delivered over 500,000 autonomous rides globally since 2017 and is focused on creating safer, greener, and more accessible urban transit.
As a Senior Software Performance Engineer on the Behavior Planning team, you will own latency, throughput, memory utilization, and thread safety for the real-time decision-making pipeline that powers autonomous vehicles. You will work alongside staff roboticists who write high-level autonomy logic, profiling the stack, enforcing performance budgets, and building execution guardrails that guarantee deterministic, high-throughput execution.
Key responsibilities include:
- Instrumenting the behavior pipeline to measure runtime performance, isolating latency spikes, resource contention, and memory inefficiencies
- Refactoring high-frequency execution loops to maximize cache utilization, eliminate dynamic memory allocations, and reduce tail latency
- Re-engineering thread boundaries and synchronization logic to maximize multi-core parallel processing while ensuring thread safety
- Building automated micro-benchmarks and runtime telemetry into CI/CD pipelines to prevent performance regressions
- Partnering with autonomy teams to establish performant, low-overhead C++ module interfaces for new behavioral features
The posting emphasizes that prior background in autonomous vehicles, controls, or robotics math is not required; the focus is on engineers obsessed with system performance, low-level execution concepts, and software profiling tools.
REQUIREMENTS:
- Deep understanding of CPU cache hierarchies (L1/L2/L3), memory alignment, lock-free concurrency models, and Linux OS thread scheduling
- Hands-on experience with Linux profiling toolchains (e.g., Perf, Tracy, eBPF) and dynamic sanitizers (ASan, TSan, Valgrind)
- Strong proficiency in modern C++ (C++17/20) with focus on low-overhead abstractions, RAII, and cache-friendly data layouts
- Familiarity with micro-benchmarking frameworks (e.g., Google Benchmark) and performance-regression testing in continuous integration
- Experience in performance-critical software environments such as game engines, financial technology, database runtimes, or operating system kernels
- B.S. Degree in Computer Science, Computer Engineering, or equivalent
DESIRABLE QUALIFICATIONS:
- Master's degree or PhD in Computer Science, Computer Engineering, or related field
- At least 5 years of professional experience
- Prior experience in AV, robotics, or high-throughput real-time control systems
- Proven track record of designing and scaling automated CI/CD performance testing infrastructure
