Applied Scientist, Wayve

Behavior and Language

Salary not provided

+ Equity

Python
Linux
C++
PyTorch
Git
Senior and Expert level
London

More information about location

2-5 days a week in office

Wayve

Autonomous mobility driven by AI

Open for applications

Wayve

Autonomous mobility driven by AI

201-500 employees

B2CB2BArtificial IntelligenceCarsTransportBig dataDeep TechRoboticsFlexible workingComputer VisionMachine LearningSaaSCloud Computing

Open for applications

Salary not provided

+ Equity

Python
Linux
C++
PyTorch
Git
Senior and Expert level
London

More information about location

2-5 days a week in office

201-500 employees

B2CB2BArtificial IntelligenceCarsTransportBig dataDeep TechRoboticsFlexible workingComputer VisionMachine LearningSaaSCloud Computing

Company mission

To reimagine autonomous mobility through embodied intelligence.

Role

Who you are

  • Thorough knowledge of and 5+ years applied experience in AI research, computer vision, deep learning, reinforcement learning or robotics
  • Ability to deliver high quality code and familiarity with deep learning frameworks (Python and Pytorch preferred)
  • Experience leading a research agenda aligned with larger goals
  • Industrial and / or academic experience in deep learning, software engineering, automotive or robotics
  • Experience working with training data, metrics, visualisation tools, and in-depth analysis of results
  • Ability to understand, author and critique cutting-edge research papers
  • Familiarity with code-reviewing, C++, Linux, Git is a plus
  • PhD in a relevant area and / or track records of delivering value through machine learning are a big plus

What the job involves

  • We are currently looking for people with research expertise in AI applied to autonomous driving or similar robotics or decision making domain, inclusive, but not limited to the following specific areas:
  • Foundation models for robotics
  • Model-free and model-based reinforcement learning
  • Offline reinforcement learning
  • Large language models
  • Planning with learned models, model predictive control and tree search
  • Imitation learning, inverse reinforcement learning and causal inference
  • Learned agent models: behavioral and physical models of cars, people, and other dynamic agents
  • You'll be working on some of the world's hardest problems, and able to attack them in new ways
  • You'll be a key member of our diverse, cross-disciplinary team, helping teach our robots how to drive safely and comfortably in complex real-world environments
  • This encompasses many aspects of research across perception, prediction, planning, and control, including:
  • How to leverage our large, rich, and diverse sources of real-world driving data
  • How to architect our models to best employ the latest advances in foundation models, transformers, world models, etc
  • Which learning algorithms to use (e.g. reinforcement learning, behavioural cloning)
  • How to leverage simulation for controlled experimental insight, training data augmentation, and re-simulation
  • How to scale models efficiently across data, model size, and compute, while maintaining efficient deployment on the car
  • You also have the potential to contribute to academic publications for top-tier conferences like NeurIPS, CVPR, ICRA, ICLR, CoRL etc working in a world-class team to achieve this

Salary benchmarks

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 headshot

Kirsty

Company Specialist at Welcome to the Jungle

Insights

Top investors

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

Leadership

Has a PhD from Cambridge in Computer Vision & Robotics. Previously Research Engineer at Skydio and Advisor to Scape Technologies

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