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May Mobility
Ann Arbor, MI - Remote
Source: May Mobility careers · View original posting
From May Mobility's posting. “We” and “our” refer to the employer.
May Mobility is transforming cities through autonomous technology to create a safer, greener, more accessible world. Based in Ann Arbor, Michigan, May develops and deploys autonomous vehicles (AVs) powered by our innovative Multi-Policy Decision Making (MPDM) technology that literally reimagines the way AVs think.
Our vehicles do more than just drive themselves - they provide value to communities, bridge public transit gaps and move people where they need to go safely, easily and with a lot more fun. We’re building the world’s best autonomy system to reimagine transit by minimizing congestion, expanding access and encouraging better land use in order to foster more green, vibrant and livable spaces. Since our founding in 2017, we’ve given more than 500,000 autonomous rides to real people around the globe. And we’re just getting started.
We’re hiring people who share our passion for building the future, today, solving real-world problems and seeing the impact of their work. Join us.
Job Summary
As a Senior Performance Engineer on the Behavior Planning team, you will own latency, throughput, memory utilization, and thread safety for our real-time decision-making pipeline. Working alongside staff roboticists who write high-level autonomy logic, your job is to profile the stack, enforce performance budgets, and build execution guardrails that guarantee deterministic, high-throughput execution.
Prior background in autonomous vehicles, controls, or robotics math is not required
. We are seeking engineers obsessed with system performance, low-level execution concepts, and software profiling tools.
Essential Responsibilities
Instrument the behavior pipeline to measure runtime performance, isolating latency spikes, resource contention, and memory inefficiencies.
Refactor high-frequency execution loops to maximize cache utilization, eliminate dynamic memory allocations, and reduce tail latency.
Re-engineer thread boundaries and synchronization logic to maximize multi-core parallel processing while ensuring thread safety.
Build automated micro-benchmarks and runtime telemetry into CI/CD pipelines to prevent algorithm developers from introducing performance regressions.
Partner with autonomy teams to establish performant, low-overhead C++ module interfaces for new behavioral features.
Required Qualifications
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 a focus on writing 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 an equivalent degree.
Desirable Qualifications
Master’s degree or PhD in Computer Science, Computer Engineering, or a 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.
Compensation
$160,000 — $180,000 USD
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