Senior ML Performance Engineer (Inference Optimisation) in London

Senior ML Performance Engineer (Inference Optimisation) in London

London Full-Time 70000 - 90000 £ / year (est.) Home office (partial)
Wayve

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: Hybrid working policy, inclusive culture, and opportunities for professional growth.
  • Other info: Dynamic environment with a focus on collaboration and innovation.
  • Why this job: Join a team tackling complex challenges in the exciting world of self-driving cars.
  • Qualifications: Experience in performance optimisation and strong software engineering skills required.

The predicted salary is between 70000 - 90000 £ per year.

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.

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.

This is a full-time role based in our office in London. At Wayve we want the best of all worlds so we operate a hybrid working policy that combines time together in our offices and workshops to fuel innovation, culture, relationships and learning, and time spent working from home.

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.

Senior ML Performance Engineer (Inference Optimisation) in London employer: Wayve

Wayve is an exceptional employer that champions innovation and collaboration in the field of Embodied AI technology. With a hybrid working policy that balances office engagement and remote flexibility, employees thrive in a culture that values diversity, continuous learning, and impactful contributions. As a Senior ML Performance Engineer, you'll have the opportunity to work on groundbreaking projects in a supportive environment that fosters professional growth and encourages you to make a meaningful difference in the world of automated driving.

Wayve

Contact Details:

Wayve Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Senior ML Performance Engineer (Inference Optimisation) in London

Tip Number 1

Network like a pro! Reach out to folks in the industry, especially those at Wayve. A friendly chat can open doors and give you insights that a job description just can't.

Tip Number 2

Show off your skills! If you've got a project or a portfolio that highlights your experience with ML performance engineering, make sure to share it during interviews. It’s a great way to demonstrate your hands-on expertise.

Tip Number 3

Prepare for technical challenges! Brush up on your knowledge of relevant stacks like TensorRT or CUDA. Be ready to discuss how you've tackled performance issues in the past—real examples will impress the interviewers.

Tip Number 4

Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in joining the Wayve team.

We think you need these skills to ace Senior ML Performance Engineer (Inference Optimisation) in London

ML Inference Optimisation
Performance Engineering
TensorRT
CUDA
Qualcomm QNN
Triton
OpenCL

Some tips for your application 🫡

Tailor Your Application:Make sure to customise your CV and cover letter to highlight your experience with ML performance optimisation. We want to see how your skills align with the role, so don’t hold back on showcasing relevant projects!

Showcase Your Technical Skills:When applying, be specific about the tools and frameworks you’ve worked with, like TensorRT or CUDA. We love seeing candidates who can confidently operate at multiple levels of abstraction, so let us know how you've done this in past roles.

Communicate Clearly:In your written application, clarity is key! We appreciate candidates who can articulate their thoughts well, especially when discussing complex topics like performance trade-offs. Keep it straightforward and engaging!

Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re keen on joining our team!

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 like TensorRT, CUDA, or Qualcomm QNN. Brush up on how these tools can optimise ML inference, as you'll likely be asked to discuss your experience with them during the interview.

Showcase Problem-Solving Skills

Prepare to discuss specific examples where you've identified bottlenecks in production systems and implemented effective solutions. Highlight your ability to work under tight constraints, as this is crucial for the role.

Communicate Clearly

Practice articulating complex technical concepts in a way that's easy to understand. You'll need to collaborate with various teams, so being able to navigate performance trade-offs and communicate effectively is key.

Demonstrate a Growth Mindset

Wayve values continuous learning and evolution. Be ready to share how you've adapted to new technologies or frameworks in the past, and express your enthusiasm for tackling complex challenges in the field of ML performance engineering.