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: Collaborative environment with a commitment to diversity and impactful contributions.
- Why this job: Join a dynamic team tackling complex challenges in automated driving technology.
- 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 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:
- 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 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) 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
- 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.
Staff ML Performance Engineer (Inference Optimisation) employer: Gravity Engineering Services Pvt Ltd.
At Wayve, we pride ourselves on being a pioneering force in the field of Embodied AI technology, offering an inclusive and dynamic work environment where your contributions truly matter. As a Staff ML Performance Engineer, you'll be at the forefront of innovation, tackling complex challenges alongside a diverse team that values collaboration and continuous learning. With ample opportunities for professional growth and a commitment to pushing the boundaries of automated driving, Wayve is not just a workplace—it's a place to define your career and make a meaningful impact.
Contact Details:
Gravity Engineering Services Pvt Ltd. Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land Staff ML Performance Engineer (Inference Optimisation)
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your projects, especially those related to ML performance engineering. This gives potential employers a taste of what you can do beyond your CV.
✨Tip Number 3
Prepare for interviews by practising common technical questions and scenarios relevant to the role. We recommend doing mock interviews with friends or using online platforms to get comfortable with the format.
✨Tip Number 4
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 our team at Wayve.
We think you need these skills to ace Staff ML Performance Engineer (Inference Optimisation)
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the role of Staff ML Performance Engineer. Highlight your experience with performance optimisation, especially in production systems. We want to see how your skills align with our needs!
Showcase Relevant Projects:Include specific projects where you've optimised ML inference or worked with edge devices. We love seeing real-world examples of your work, so don’t hold back on the details!
Craft a Compelling Cover Letter:Your cover letter should tell us why you’re excited about working at Wayve and how you can contribute to our mission. Be genuine and let your passion for AI and performance engineering shine through!
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’s super easy!
How to prepare for a job interview at Gravity Engineering Services Pvt Ltd.
✨Know Your Tech Stack
Make sure you’re well-versed in the relevant stacks and toolchains mentioned in the job description, like TensorRT and 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 tackled performance issues under tight constraints. Be ready to explain how you identified bottlenecks and the steps you took to resolve them. This will demonstrate your hands-on experience and ability to think critically.
✨Communicate Clearly
Since collaboration is key in this role, practice articulating your thoughts clearly. You might need to explain complex technical concepts to non-technical stakeholders, so being able to simplify your explanations will be a huge plus.
✨Embrace the Challenge
Wayve values those who lean into complex challenges. Prepare to discuss how you approach uncertainty and problem-solving in high-pressure situations. Share examples that highlight your resilience and adaptability in fast-paced environments.
