At a Glance
- Tasks: Optimise ML inference for edge devices and contribute to groundbreaking AI projects.
- Company: Wayve, a leader in Embodied AI technology with a focus on innovation.
- Benefits: Competitive salary, inclusive culture, and opportunities for professional growth.
- Other info: Dynamic environment with a commitment to diversity and collaboration.
- Why this job: Join a team tackling complex challenges to shape the future of automated driving.
- Qualifications: Experience in performance optimisation and strong software engineering skills required.
The predicted salary is between 60000 - 80000 £ 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 Senior 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 contribute to 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
- Profile and pinpoint bottlenecks across the full inference stack (model graph, compiler/runtime, kernel execution, memory movement) and deliver measurable improvements.
- Implement and validate optimisations in compilers, runtimes, and/or kernels (e.g. operator fusion, scheduling, quantisation-aware performance, custom kernels).
- Build robust benchmarking and regression testing to ensure performance improvements hold across models, devices, and software releases.
- Optimise for multiple targets (e.g. NVIDIA Orin/Thor, Qualcomm) and work with teams to support these in a maintainable way.
- Collaborate with model developers to influence architecture and training/deployment decisions that affect on-device performance.
- Contribute to team 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) 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 discuss and navigate performance trade-offs with stakeholders.
Desirable
- 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.
- Some experience supporting or informally mentoring other engineers.
Senior ML Performance Engineer (Inference Optimisation) employer: Wayve
At Wayve, we pride ourselves on being a forward-thinking employer that champions innovation and collaboration in the field of AI technology. Our inclusive work culture fosters diversity and encourages continuous learning, providing employees with ample opportunities for professional growth while tackling complex challenges in a fast-paced environment. Located in a vibrant tech hub, we offer a unique chance to contribute to groundbreaking projects that shape the future of automated driving, making your work here not just a job, but a meaningful career journey.
StudySmarter Expert Advice🤫
We think this is how you could land Senior ML Performance Engineer (Inference Optimisation)
✨Tip Number 1
Network like a pro! Attend industry meetups, conferences, or online webinars related to ML and AI. Engaging with professionals in the field can open doors and give you insights that job boards just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to ML inference optimisation. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice explaining complex concepts simply, as communication is key in collaborative environments like Wayve.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, it shows you're genuinely interested in being part of our mission at Wayve.
We think you need these skills to ace Senior ML Performance Engineer (Inference Optimisation)
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the role of Senior ML Performance Engineer. Highlight your experience with performance optimisation, especially in production systems, and any relevant tools like TensorRT or CUDA. We want to see how your skills align with our needs!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about optimising ML inference and how your background makes you a great fit for Wayve. Keep it concise but impactful—let us know what drives you!
Showcase Your Projects:If you've worked on projects that involved ML systems or edge devices, make sure to showcase them. We love seeing real-world applications of your skills, so include any benchmarks or performance improvements you've achieved. It helps us understand your hands-on experience!
Apply Through Our Website:We encourage you to apply through our website for the best chance of getting noticed. It streamlines the process for us and ensures your application lands in the right hands. Plus, it shows you're keen on joining our team at Wayve!
How to prepare for a job interview at Wayve
✨Know Your Tech Stack
Make sure you’re well-versed in the relevant stacks and toolchains mentioned in the job description, like TensorRT or CUDA. Brush up on your knowledge of how these tools can optimise ML inference, as you'll likely be asked to discuss specific examples from your experience.
✨Showcase Problem-Solving Skills
Prepare to discuss past projects where you identified and resolved performance bottlenecks. Be ready to explain your thought process and the measurable improvements you achieved, especially under tight constraints like latency and memory.
✨Communicate Clearly
As a Senior ML Performance Engineer, collaboration is key. Practice articulating complex technical concepts in a way that’s easy for non-experts to understand. This will help you demonstrate your ability to work with diverse teams and stakeholders.
✨Embrace the Challenge
Wayve values those who lean into complex challenges. Prepare to discuss how you've tackled difficult problems in the past and what you learned from those experiences. Show them that you’re not afraid of uncertainty and are eager to contribute to groundbreaking solutions.
