Principal Machine Learning Engineer, Wayve
Scenario Technology
2-5 days a week in office (Sunnyvale, CA)
Autonomous mobility driven by AI
Be an early applicant
Autonomous mobility driven by AI
201-500 employees
Be an early applicant
2-5 days a week in office (Sunnyvale, CA)
201-500 employees
Company mission
To reimagine autonomous mobility through embodied intelligence.
Role
Who you are
- M.S. or Ph.D. in Computer Science, Machine Learning, or related fields, with 10+ years of industry experience
- Proven experience in building, deploying, and scaling production-level ML solutions
- Deep understanding of ML fundamentals with expertise in one or more areas: Deep Learning, Computer Vision, Traditional ML, or Large Language Models
- Proficiency in Python, with a strong focus on clean, well-structured, and testable code
- Experience leading and executing large-scale, cross-functional projects
- 7+ years of experience in ML engineering and 4+ years in production deployments
- Hands-on experience with data pipelines, SQL, and managing large-scale databases
Desirable
- 3+ years of experience in simulation, perception, or autonomous driving technologies
- Familiarity with training and evaluating autonomous vehicle models
- Industry experience in autonomous vehicles, robotics, transportation, or computer vision
What the job involves
- We’re revolutionizing the way autonomous vehicles learn and operate, and the Scenario Technology and Coverage team plays a pivotal role in that mission by building scalable, data-driven scenarios for evaluating and validating self-driving models
- As a Principal ML Engineer on the Scenario Technology and Coverage team, you'll lead the design and implementation of scalable ML-based tools that enhance our scenario pipeline—from data mining and scenario generation to simulation-based evaluation
- Your work will be critical in ensuring that our driving models are thoroughly tested and optimized across diverse and realistic conditions
- Lead the development of robust ML models and augmentation techniques that power our scenario generation and validation systems
- Architect scalable systems for mining, curating, and synthesizing data to fuel scenario databases, using both real-world and synthetic data
- Collaborate with cross-functional teams, including Simulation and Science, to integrate state-of-the-art technologies into our scenario pipelines
- Drive innovation in scenario coverage, focusing on both closed-loop and open-loop evaluations
- Own end-to-end technical solutions: from translating product requirements into engineering tasks to delivering high-impact ML models and infrastructure improvements
- Identify and address infrastructure gaps, leading initiatives to enhance our foundational tools
- Guide the team in navigating complex technical challenges and setting the technical direction in scenario technology
- Mentor engineers across teams, fostering growth and innovation in scenario-driven ML engineering
Our take
Wayve is developing artificial intelligence (AI) that teaches cars to drive autonomously using reinforcement learning, simulation, and computer vision. Wayve’s core premise is that the big breakthrough in self-driving cars will come from better AI brains rather than more sensors or “hand-coded” rules which it believes are highly restrictive and not at all scalable.
The company said that it trains its autonomous driving system using simulated environments and then transfers that knowledge into the real world, where it emulates how humans adapt to conditions in real time. It ultimately relies on end-to-end deep learning AI rather than hard-engineered AI. This is one of the world's hardest problems to solve, but Wayve has made an exciting start and is taking a very different approach to competitors like Uber and Waymo, who are relying more on sensors.
Following a few years of innovative breakthroughs, Wayve now has backing from high-profile investors such as Microsoft and angels, including Uber's chief scientist Zoubin Ghahramani and Pieter Abbeel, a UC Berkeley robotics professor and pioneer of deep reinforcement learning. The company's strategic partnerships with outfits like Asda and Ocado to test-run autonomous deliveries, as well as publicity through the Minister is a show of confidence in the future of Wayve's solution to autonomous driving.
Kirsty
Company Specialist at Welcome to the Jungle
Insights
Some candidates hear
back within 2 weeks
28% female employees
24% employee growth in 12 months
Company
Funding (last 2 of 7 rounds)
May 2024
$1.1bn
SERIES C
Jan 2022
$200m
SERIES B
Total funding: $1.3bn
Company benefits
- Learning budget
- In-house chef
- Flexible Working
- Private health insurance and therapy
- Workplace nursery scheme
- Onsite bar
- Large social budgets
- Enhanced parental leave
Company values
- Pave new roads, explore unknown horizons: We take calculated risks and embrace unknown territory
- Leave positive tracks: A big reason for working on autonomous vehicles is for the positive impact they can have to the environment, the lives they will save, the opportunities they will create for others and more!
- Autonomous in thought, collective in action: We are built of strong, curious individuals coming from all walks of life, but who, together, want to achieve a common goal.
- Drive each other forward: We are a company that stands strong upon the foundation which it has created. This foundation is the team, the individuals who make Wayve, Wayve.
Company HQ
London, UK
Articles
Leadership
Alex Kendall
(CEO)Has a PhD from Cambridge in Computer Vision & Robotics. Previously Research Engineer at Skydio and Advisor to Scape Technologies
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