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, we need to provide the fastest, most affordable and most convenient routes and provide an accurate ETA (estimated time of arrival). We achieve this by leveraging our fleet and collecting in real-time millions of data points such as imagery, locations, speeds, etc and by integrating the results with 3rd party data such as closures and events.

To strengthen our efforts, we are hiring a Staff Machine Learning Engineer who will work on architecting and deploying ML-based workflows and cloud services. 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 data-engineering 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 optimal route and an accurate ETA. 

• Own and drive a large part of the team’s technical roadmap based on technology and our business needs.
• Enable collaboration across multiple teams and functions to deliver on cross-team initiatives while delegating ownership and uplifting those around you
• Grow software engineers via mentoring and exemplify execution and delivery focused leadership
• Set an example for an inclusive engineering culture
• Build and deploy machine learning approaches to improve our routes & ETAs.
• Build and deploy mission-critical data pipelines that can serve thousands of requests per second.
• Plan and execute experiments to enable the team to make data-driven decisions
• 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.

• 6+ years of experience building machine learning algorithms at scale, deep learning and their tools and learning frameworks. 
• Experience in developing and deploying scalable tools and services to handle machine learning training and inference.
• Experience in translating business needs into technical solutions.
• Experience with providing technical guidance for multiple teams. 
• Experience with cloud computing using AWS, GCP or Azure and building microservice-based architectures.
• Experience with workflow orchestration tools such as Apache Airflow.
• Strong verbal and written communication skills with proven ability to uplift others.

• Pension scheme with 4% employer contribution
• Risk and Accidental Death & Dismemberment benefits
• Mental health benefits 
• Family building benefits
• 18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible
• 30 days for paid time off in addition to 10 observed holidays

This role will be in-office on a hybrid schedule if an established Lyft Location is available to the Munich region — Hybrid Team Members will be expected to work in the office 3 days per week on Mondays, Thursdays and a team-specific third day. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year.

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.