At a Glance
- Tasks: Optimise ML inference for edge devices and contribute to groundbreaking AI projects.
- Company: Wayve, a leader in Embodied AI technology for automated driving.
- Benefits: Inclusive culture, diverse team, and opportunities for impactful contributions.
- Other info: Dynamic environment with a focus on learning and career growth.
- Why this job: Join us to shape the future of self-driving cars and make a real difference.
- Qualifications: Experience in performance optimisation and strong software engineering skills required.
The predicted salary is between 72000 - 88000 £ per year.
About us
Founded in 2017, Wayve is the leading developer of Embodied AI technology. Our advanced AI software and foundation models enable vehicles to perceive, understand, and navigate any complex environment, enhancing the usability and safety of automated driving systems. Our vision is to create autonomy that propels the world forward. Our intelligent, mapless, and hardware-agnostic AI products are designed for automakers, accelerating the transition from assisted to automated driving. In our fast-paced environment big problems ignite us—we embrace uncertainty, leaning into complex challenges to unlock groundbreaking solutions. We aim high and stay humble in our pursuit of excellence, constantly learning and evolving as we pave the way for a smarter, safer future. At Wayve, your contributions matter. We value diversity, embrace new perspectives, and foster an inclusive work environment; we back each other to deliver impact. Make Wayve the experience that defines your career!
The role
As a Staff ML Performance Engineer, you’ll play a key role in high-impact projects, optimising ML inference for edge accelerators and GPUs. The focus of this team is to run large transformer-based models efficiently on low-cost, low-power edge devices to enable Wayve’s first driving product. You’ll help set the technical direction for turning these models into production systems that run reliably on in-vehicle compute. This is a hands-on role working across ML systems, compilers, runtimes, kernels, and embedded deployment, contributing to several early-stage, high-impact projects at Wayve.
Key responsibilities:
- Identify, implement and validate optimisations in ML compilers, runtimes, and kernels (e.g. operator fusion, scheduling, quantisation-aware performance, custom kernels).
- Profile and pinpoint bottlenecks across the full inference stack (model graph, compiler/runtime, kernel execution, memory movement) and deliver measurable improvements.
- Build robust benchmarking and regression testing to ensure performance improvements hold across models, devices, and software releases.
- Develop and optimise for multiple target platforms (e.g. NVIDIA Orin/Thor, Qualcomm), working with cross-functional teams to deliver performant and maintainable solutions.
- Collaborate with model developers to influence architecture and training/deployment decisions that affect on-device performance.
- Contribute to technical roadmaps and tooling and help raise the standard of performance engineering across the team.
About you
Essential
- Proven experience improving performance in production systems with tight constraints (latency, memory, bandwidth, power/thermal, or cost).
- Strong proficiency with at least one relevant stack/toolchain (e.g. TensorRT, CUDA, Qualcomm QNN, Triton, OpenCL, MLIR, ONNX) and confidence learning adjacent frameworks quickly.
- Comfort operating at multiple levels of abstraction — from high-level model behaviour down to low-level kernel/runtime execution.
- Strong software engineering fundamentals (debugging, profiling, testing, and maintainable code).
- Clear communicator and collaborative teammate; able to align multiple stakeholders on performance trade-offs and priorities.
Desirable
- Experience with compute graph scheduling and execution on multiple targets.
- Exposure to embedded or edge deployment of ML models, including benchmarking on real devices and handling system-level constraints.
- Experience with NVIDIA and/or Qualcomm SoCs and performance tooling.
- Python and C++ proficiency.
- Experience mentoring others and/or driving technical direction in a small, fast-moving team.
Wayve is committed to creating an inclusive interview experience. If you require any accommodations or adjustments to participate fully in our interview process, please let us know. We understand that everyone has a unique set of skills and experiences and that not everyone will meet all of the requirements listed above. If you’re passionate about self-driving cars and think you have what it takes to make a positive impact on the world, we encourage you to apply.
At Wayve we're committed to creating a diverse, fair and respectful culture that is inclusive of everyone based on their unique skills and perspectives, and regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, veteran status, pregnancy or related condition (including breastfeeding) or any other basis as protected by applicable law.
Staff ML Performance Engineer (Compiler) employer: Wayve
Wayve is an exceptional employer that fosters a dynamic and innovative work culture, where software engineers can thrive while contributing to cutting-edge AI solutions. With a strong emphasis on employee growth, Wayve offers opportunities for professional development and collaboration in a hybrid work environment, allowing for flexibility and work-life balance. Located in a vibrant tech hub, employees benefit from a supportive community and access to industry-leading resources.