At Lyft, our mission is to improve people’s lives with the world’s best transportation. 

Our transport network serves the needs of millions of people every day who want to get from one place to another using Lyft cars, bikes and scooters, with public transportation, or on foot. To serve these needs in the best possible way we maintain a map that is reflecting our constantly changing environment. Our systems draw knowledge distilled from all the data points collected every minute - driving locations, sensor data, and user feedback. This empowers us to use the map and answer questions such as: Which route should be taken? Which transport mode is ideal in this location? Has the event in my town resulted in road closures? Is a U-turn allowed at that specific location? Is the drop-off location considered safe? And many more.

To strengthen our efforts, we are hiring a Machine Learning Engineer who will work end-to-end on creating new capabilities to detect changes in the environment and reflect them in our Lyft map using a wide variety of input sources from the Lyft fleet (image, telemetry, ...). For this we are looking for someone who is fluent with state of the art machine learning approaches, who values software engineering best practices and also loves the algorithmic and geospatial side of the challenge. 

Our technology stack involves deep learning toolkits like PyTorch and relies on technologies like Kubernetes to leverage the models at large scale. You will work with incredibly passionate and talented colleagues from machine learning, data science, and engineering on projects that delight our passengers and drivers – powered by an up to date map. 

• Build and deploy machine learning approaches to automatically update our Lyft map.
• Build and deploy mission-critical data pipelines that can serve thousands of requests per second.
• Stay informed about latest research in machine learning and transform academic approaches into productionized systems that produce reliable results within a large-scale sensor-processing system.
• Help establish technical roadmaps and architectures based on technology and our business needs.

• Experience with machine learning algorithms, deep learning, and their tools and learning frameworks (e.g. PyTorch).
• Experience in deep learning architectures and foundation models (especially Vision and Large Language Models).
• Experience in developing and deploying scalable tools and services to handle machine learning training and inference.
• Proven work experience in software engineering.

• Pension scheme with 4% employer contribution
• Risk and Accidental Death & Dismemberment benefits
• Mental health benefits 
• 18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible
• 30 days for paid time off

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.