Computer Vision Engineer - Mapping (Autonomous) - London

At Lyft, our mission is to improve people’s lives with the world’s best transportation. To do this, we start with our own community by creating an open, inclusive, and diverse organization.

From day one, Lyft’s mission has been to improve people’s lives with the world’s best transportation. And self-driving cars are critical to that mission: they can make our streets safer, cities greener, and traffic a thing of the past. That’s why we started Level 5, our self-driving division, where we’re building a self-driving system to operate on the Lyft network.

Level 5 is looking for doers and creative problem solvers to join us in developing the leading self-driving system for ridesharing. Our team members come from diverse backgrounds and areas of expertise, and each has the opportunity to have an outsized influence on the future of our technology. Our world-class software and hardware experts work in brand new garages and labs in Palo Alto, California, and offices in London, England and Munich, Germany. And we’re moving at an incredible pace: we’re currently servicing employee rides in our test vehicles on the Lyft app. Learn more at lyft.com/level5.

Having a network driving hundreds of millions of miles every year is our key advantage: we leverage this wealth of experience to equip self-driving cars with prior knowledge of the complex driving environments, so that they can navigate them safely. This knowledge comes in the form of accurate 3D maps encoding road topology and traffic rules, like which lanes need to yield to oncoming traffic, and behavioral data, i.e. how human drivers react to different traffic situations and their driving patterns. It is the fuel powering the next generation algorithms responsible for the decision making of self-driving cars. 

The mission of the London Mapping team is to generate maps and behavioural data at unprecedented scale. We develop cutting-edge computer vision and machine learning technology to do this accurately from commodity sensors, which could be deployed on every car. And we build the scalable distributed systems that process the data collected by large fleets of vehicles and aggregate it in the cloud.

• Collaborate with other Computer Vision and Machine Learning engineers on high-impact projects and innovative new solutions to problems in self-driving and mapping
• Develop cutting-edge machine learning models and mapping algorithms operating on visual and low-cost sensor data
• Develop the distributed systems to do this at very large scale, extracting knowledge from one of the largest rideshare networks in the world
• Use this knowledge to accelerate and develop the next generation of autonomous driving technology

• 3 years + experience working on one or more areas of 3D Computer Vision, such as: 
• Structure-from-Motion 
• SLAM 
• 3D reconstruction
• Localisation 
• 3D perception
• Object recognition
• Tracking
• Deep Learning
• Image classification
• Programming experience in Python or C++
• Experience using AWS or related cloud technologies (e.g. GCP, Azure)

• Private health insurance, income protection, and life assurance benefits
• Mental health benefits
• Cycle to Work scheme option to purchase a bike and accessories tax free
• Unlimited holiday
• 9 bank holidays
• Pension scheme with 5% employer contribution
• 18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible

Lyft proudly pursues and hires a diverse workforce. Lyft believes that every person has a right to equal employment opportunities without discrimination because of race, ancestry, place of origin, colour, ethnic origin, citizenship, creed, sex, sexual orientation, gender identity, gender expression, age, marital status, family status, disability, pardoned record of offences, or any other basis protected by applicable law or by Company policy.  Lyft also strives for a healthy and safe workplace and strictly prohibits harassment of any kind. Accommodation for persons with disabilities will be provided upon request in accordance with applicable law during the application and hiring process. Please contact your Recruiter if you wish to make such a request.