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