Senior Machine Learning Engineer

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.

Our transportation network serves millions daily, relying on a map that reflects the constantly changing real world. Our systems leverage insights from driving locations, sensor data, and user feedback to provide the best possible service. This empowers us to optimize routes, recommend ideal transport modes, ensure safe drop-off locations, and much more.

To strengthen our efforts, we are hiring a Senior ML Engineer who will work end-to-end on creating and improving 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. For this we are looking for someone who values software engineering best practices, loves the algorithmic and geospatial side of the challenge and is data-driven from start to end. 

Our technology stack ranges from basic machine learning models to large language models and running them at scale on millions of images. 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. 

Responsibilities:

• Design, develop, deploy, monitor, operate and maintain scalable, robust, stable, reliable and performant systems to support map data pipelines that operate on large data sets.
• Provide technical leadership and direction to the team by defining the team’s roadmap, architecture, processes, and best practices, with a focus on scalability and robustness in data pipeline design and implementation for large geospatial datasets.
• Analyze our internal systems and processes, locate areas for improvement/automation, and build tools and dashboards to provide visibility.
• Write clean, testable, and maintainable code while implementing best practices for code reviews, CI/CD pipelines, and system observability.
• Help establish technical roadmaps and architectures based on technology and our business needs.
• Drive high-impact projects and innovate new solutions to provide the best mapping experience possible.
• Ship ML models at scale and low cost by focussing on systems / performance engineering.
• Create resilient and scalable infrastructure that enables rapid iteration of new pipelines and  machine learning models.

Experience:

• BS/MS or equivalent degree in Computer Science, Machine Learning, or a related field.
• 5+ years of experience building machine learning algorithms at scale, deep learning and their tools and learning frameworks. 
• Extensive experience with Python (including its data related batteries like numpy or pandas).
• Familiarity with cloud platforms such as AWS and/or GCP, including experience with cloud infrastructure.
• Excellent communication and collaboration skills with experience working in cross-functional teams.
• Excellent analytical and problem-solving skills with a passion for tackling complex challenges.
• Proven track record of proactively driving initiatives, taking ownership of projects, and independently identifying and implementing improvements.
• Advantageous would be:
  • Experience with MLOps processes
  • Familiarity with geospatial data processing, GIS frameworks, or mapping infrastructure
  • Familiarity with Go

Benefits:

• 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

Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. 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, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid

Lyft is committed to creating an inclusive workforce that fosters belonging. 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.