Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Staff Machine Learning Performance Engineer, Inference Optimisation

Wayve
City of London
3 weeks ago
Create job alert
Staff Machine Learning Performance Engineer, Inference Optimisation

London


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.


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/Principal ML Performance Engineer, you’ll lead high‑impact projects optimising ML inference for edge accelerators and GPUs. The focus of this team is to run large transformer‑based models efficiently in low‑cost, low‑power edge devices to enable Wayve’s first driving product. This is an exciting opportunity to lead in several high‑impact, early‑stage projects at Wayve, operating at the intersection of ML Compilers, Kernels, and ML engineering.


Key responsibilities:



  • You’ll identify opportunities for improvement in the ML compiler and/or kernels and implement
  • Develop with multiple target platforms in mind e.g. Nvidia (Thor, Orin), Qualcomm, etc
  • You’ll build technical roadmaps and work with teams to execute against them
  • You’ll collaborate closely with model developers and software engineers in other teams across the business
  • You’ll have the opportunity to develop new skills and experience

About you

  • Experience solving optimisation problems (e.g. developing systems with latency or other resource constraints)
  • Experience with any of (or similar): MLIR, TensorRT, Cuda, Qualcomm QNN, Cuda, OpenCL, Triton
  • Experience leading technical teams (5+ people)
  • Excellent interpersonal and communication skills
  • Experience with Nvidia and Qualcomm SoCs and frameworks are valuable, but not required
  • Experience in ML development is valuable, but not required
  • Proficiency with Python/C++

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. We operate core working hours so you can determine the schedule that works best for you and your team.


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.


DISCLAIMER: We will not ask about marriage or pregnancy, care responsibilities or disabilities in any of our job adverts or interviews. However, we do look to capture information about care responsibilities, and disabilities among other diversity information as part of an optional DEI Monitoring form to help us identify areas of improvement in our hiring process and ensure that the process is inclusive and non‑discriminatory.


#J-18808-Ljbffr

Related Jobs

View all jobs

Staff Machine Learning Engineer

Machine Learning Engineer (Databricks)

Staff Machine Learning Platform/Ops Engineer Location: London

Staff Machine Learning Engineer - Autonomy

Senior RF Data Scientist / Research Engineer

Principal Data Engineer

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Neurodiversity in Machine Learning Careers: Turning Different Thinking into a Superpower

Machine learning is about more than just models & metrics. It’s about spotting patterns others miss, asking better questions, challenging assumptions & building systems that work reliably in the real world. That makes it a natural home for many neurodivergent people. If you live with ADHD, autism or dyslexia, you may have been told your brain is “too distracted”, “too literal” or “too disorganised” for a technical career. In reality, many of the traits that can make school or traditional offices hard are exactly the traits that make for excellent ML engineers, applied scientists & MLOps specialists. This guide is written for neurodivergent ML job seekers in the UK. We’ll explore: What neurodiversity means in a machine learning context How ADHD, autism & dyslexia strengths map to ML roles Practical workplace adjustments you can ask for under UK law How to talk about neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in ML – & how to turn “different thinking” into a genuine career advantage.

Machine Learning Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we move into 2026, the machine learning jobs market in the UK is going through another big shift. Foundation models and generative AI are everywhere, companies are under pressure to show real ROI from AI, and cloud costs are being scrutinised like never before. Some organisations are slowing hiring or merging teams. Others are doubling down on machine learning, MLOps and AI platform engineering to stay competitive. The end result? Fewer fluffy “AI” roles, more focused machine learning roles with clear ownership and expectations. Whether you are a machine learning job seeker planning your next move, or a recruiter trying to build ML teams, understanding the key machine learning hiring trends for 2026 will help you stay ahead.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.