Applied Scientist, Wayve

Reinforcement Learning & Reward Modeling

Salary not provided

+ Stock options

Python

PyTorch

Senior and Expert level

Vancouver

More information about location

2-5 days a week in office

Autonomous mobility driven by AI

Job no longer available

Autonomous mobility driven by AI

501-1000 employees

B2CB2BArtificial IntelligenceCarsTransportBig dataDeep TechRoboticsFlexible workingComputer VisionMachine LearningSaaSCloud Computing

Job no longer available

Salary not provided

+ Stock options

Python

PyTorch

Senior and Expert level

Vancouver

More information about location

2-5 days a week in office

501-1000 employees

B2CB2BArtificial IntelligenceCarsTransportBig dataDeep TechRoboticsFlexible workingComputer VisionMachine LearningSaaSCloud Computing

Company mission

To reimagine autonomous mobility with embodies intelligence, aiming to lead the world into a new era of autonomy.

Job

Company

Role

Who you are

The ideal candidate has a deep understanding of reinforcement learning, machine learning, and behavioural modelling, combined with a drive to innovate in the autonomous driving space
Proven expertise in reinforcement learning, including in areas like offline RL, reward modeling, RLHF, DPO, GPRO, as well as experience with machine learning
Strong programming skills in Python and experience with machine learning libraries such as PyTorch
Experience in working with simulation environments and real-world data for model validation and performance benchmarking
Demonstrated ability to publish research and present findings to both technical and non-technical audiences at top tier conferences
Excellent problem-solving skills and the ability to work independently as well as in a team environment
Demonstrated ability to work collaboratively in a fast-paced, innovative, interdisciplinary team environment

Desirable

Track record of publications at top-tier conferences like NeurIPS, CVPR, ICRA, ICLR, CoRL etc
Familiarity with self-driving technologies, sensor data processing, and real-time decision-making algorithms
Experience with large-scale machine learning systems, distributed training and deploying models in production environments

What the job involves

We're looking for an experienced Applied Scientist with expertise in Reinforcement Learning and Reward Modelling to advance our training and evaluation frameworks contributing significantly to the creation of safe and reliable AI driving technology
In this role, you will be at the forefront of designing and optimizing reward and reinforcement learning models that are powerful and resource-efficient, tailored for the unique demands of embodied AI and autonomous systems
Design, develop, and refine reward models that align with safe and efficient driving objectives for autonomous vehicles
Work closely with multidisciplinary teams to integrate reward models with real-world data and simulation frameworks
Define a data strategy that includes efficient use of real and synthetic data, annotations, and active learning
Design experiments to evaluate reward structures in diverse driving scenarios and identify areas for improvement
Collaborate with world-class researchers and engineers to push the boundaries of AI, contributing significantly to the evolution of autonomous driving technology

Our take

Wayve is developing 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

Top investors

28% female employees

24% employee growth in 12 months

Glassdoor (4.6)

Company

Funding (last 2 of 8 rounds)

Feb 2026

$1.2bn

SERIES D

May 2024

$1.1bn

SERIES C

Total funding: $2.5bn

Company benefits

Private healthcare: Choose our optional health insurance for comprehensive coverage for you and your family.
Paid time off: Paid vacation plus public holidays and additional leave programs, ensuring you have time to unwind.
Mental health resources: Through Spill, you can access therapy and mental health support.
Community and socials: Join clubs or attend team socials to connect over hobbies, sports, or just for fun.
Competitive compensation: Our compensation package includes cash and equity, making you a true partner in our success.
Learning and development: Budgets for books, courses, and company-wide training to support your continuous growth.

Company HQ

London, UK

Leadership

Alex Kendall

(Co-Founder & CEO)

Alex has a PhD from Cambridge in Computer Vision & Robotics. Prior to Wayve, he was a Research Fellow at Trinity College, a Scientific Advisor at Scape Technologies, a Research Engineer at Skydio, and a Software Engineer at Beca.

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