Estimation Engineer, Controls

Job Description

Who we are

We’re building artificial intelligence capable of complex driving using end-to-end deep learning; one which can scale across diverse urban environments. Wayve is building a full driving software system which is data-driven at every layer, learning to drive. Our unique end-to-end machine learning approach learns to drive in complex, never-seen-before urban environments. We learn to drive with computer vision by both observing human driving, and by using reinforcement learning.

This is one of the world’s hardest and most impactful problems to solve. Which is why we’re building a diverse, world-class team of people who are motivated by the opportunity to work with brilliant people on challenging problems that leave a positive impact on society.

Where you will have an impact

As an estimation engineer your focus will be on the algorithms which provide estimates of various key data required by other parts of the AV stack. Some examples include vehicle motion (pose, velocities, accelerations), parameters which govern the vehicle dynamics, and calibrations of sensors. As such, your work will have direct impact on how well our cars drive.

You will write both real-time software to run on our robots and offline software for post-hoc estimation, visualisation and analysis.

You will work with a small team to write code, debug hard problems which impact real world applications and help us win the space-race of the 2020’s: Autonomous Driving. If you have experience as a Software Engineer, Systems Engineer, Production Engineer, Site Reliability Engineer, or Robotics Engineer with a focus on performance and systems you’ll be well prepared for this role, but we encourage anyone who’s passionate about systems, scale and reliability to apply!

Working in the Robotics team, you will be responsible for building, deploying and tuning estimation algorithms. This includes responsibilities like:

• Writing, testing and validating high performance real-time software
• Building analysis tools to visualise your algorithms’ performance and refine estimates
• Fine-tuning algorithms in test track or on-road environments
• Building monitoring solutions to visualise performance of your algorithms at scale and identify issues quickly

What you will bring to Wayve

• Experience building real time systems for robotics, autonomy, AR/VR or related field
• Practical, hands-on experience with debugging systems / algorithms in the field
• Strong modern C++ and Python
• PhD or MSc in robotics, computer science, engineering or related field

Nice to haves:

• Experience or knowledge in any of: machine learning, state estimation (including but not limited to Kalman filtering), SLAM, perception, prediction, motion planning, control
• Technical leadership experience, e.g. where you led a project, team, feature development or trial
• Knowledge of modern machine learning techniques is a plus, but not a requirement for this role

What we offer you

• Competitive compensation with salary and equity

• Immersion in a team of world-class researchers, engineers and entrepreneurs

• A position to shape the future of autonomous driving and to tackle the biggest challenges of our time

• Benefits such as an onsite chef, workplace nursery scheme, private health insurance, therapy, daily yoga, onsite bar, large social budgets, unlimited L&D requests, enhanced parental leave, and more!

• This is a full-time role based in our office in King’s Cross. If your role is possible to do remotely we support flexible working, including working for up to 2 weeks from anywhere in the world. We trust you to know what works best for your team and projects and ask that you have a healthy presence that enables the right meetings to happen in person and strong relationships to be built.

Wayve is built on people and their differences gives us strength. We are proud to be an equal opportunities workplace and encourage people from all walks of life to join our journey, growing and expanding with us. We don't just embrace diversity, we encourage it.