Metromile is a tech company on the forefront of disrupting a $250 billion auto insurance category that has gone unchanged for over 80 years. As an insurtech powered by data science and customer-centric design, we’re building a community of drivers who come for the savings and stay for the experience. With technology at its core, Metromile is reimagining insurance to make it fairer and actually delightful. We’re obsessed with savings, service, and features -- street sweeping alerts, monthly mileage summaries, fuel trackers and more -- that engage a customer all along their journey. The team is growing quickly across its San Francisco, Tempe, and Boston offices.
Named a Glassdoor Best Place to Work two years in a row, our CEO consistently has a 95+ percent approval rating; nearly 90% say they’d recommend Metromile to a friend.
About the role
The Machine Learning Platform Engineering team is in charge of maintaining, scaling, and optimizing all of the operations involved in the machine learning development cycle. Our models process data from a variety of sources and rely heavily on terabytes of unstructured vehicle telematics data comprising billions of trips, creating unique challenges for this platform. As an ML Platform Engineer you will be responsible for designing, implementing and deploying backend systems and tools to support ML workflows. You will work closely with data scientists and other engineers to help build a platform that will boost Metromile’s competitive advantage in ML and AI technology.
We are looking for someone who is innovative, self-motivated and takes initiative. The ideal candidate will be a team player and will work well in a collaborative environment where the open sharing of ideas is encouraged. Clear and effective communication skills are also key, as this role will interface with other engineering teams and business stakeholders, in addition to data scientists.
- Help build a platform for feature extraction, machine learning model training, batch and real-time evaluation, automated re-training, continuous monitoring and deployment in a micro-service architecture.
- Work with product managers, backend, frontend and data engineering teams to ensure clear requirements and fast productization of models.
- Develop Python libraries and tools to support machine learning workflows.
- Help optimize and scale code for machine learning models that process terabytes of trip data daily.
- Work with data scientists to establish the best coding practices, such as code quality, code review processes, and unit testing.
- Stay up to date with developments in the field and be responsible for testing and implementing new technologies.
- 4+ years experience in building machine learning platforms or products.
- Excellent communication skills and team player.
- Experience with workflow management tools such as Airflow, AWS Batch, Luigi or similar technology.
- Familiarity in data-oriented programming such as Spark, Python, SQL with solid understanding of query performance and tuning.
- Fluent in Python.
- Experience working with Docker containers and Kubernetes.
Nice to haves:
- Experience with machine learning libraries and frameworks like xgboost, pyTorch, tensorflow, Keras, Caffe2, scikit-learn, H2O.
- Knowledge and experience building machine learning algorithms.
What’s in it for you
- Competitive salary plus equity.
- Robust benefit options (health, dental, vision, 401K).
- Commuter and well-being benefits.
- Generous parental leave.
- Catered lunches and a fully stocked kitchen.
- Monthly social events (Movies, game nights, park days, etc.).
- Mac equipment and adjustable workstations.
Metromile is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation.
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.