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Senior Machine Learning Engineer

Engineering · Full-time · San Francisco, United States

Metromile recently launched a new B2B business venture, Metromile Enterprise, to license its proprietary AI platform to insurance companies in the US and across the globe. We are looking for a Senior Machine Learning Engineer to join the team developing and launching cutting-edge ML models solving some of the most challenging problems in the personal and commercial insurance industry. This role will work closely with the Data Science and engineering team to deploy and monitor the systems that let our models power business decisions in real time.

If you are excited by the opportunity to explore diverse data sources and collaborate with technical and non-technical team members and stakeholders, we’d love to hear from you!

About Us

Metromile is a leading digital insurance platform in the United States. With data science as its foundation, Metromile offers real-time, personalized auto insurance policies by the mile, instead of the industry-standard approximations and estimates that have historically made prices unfair. Metromile’s digitally native offering is built around the modern driver’s needs, featuring automated claims, complimentary smart driving features and annual average savings of 47% over what they were paying their previous auto insurer.

In addition, through Metromile Enterprise, it licenses its technology platform to insurance companies around the world. This cloud-based software as a service enables carriers to operate with greater efficiency, automate claims to expedite resolution, reduce losses associated with fraud, and unlock the productivity of employees.

Thanks to what makes us different -- our people and our technology -- we’ve been honored with a slew of awards. A few recent ones include: named a Benzinga “Best Insurtech” finalist, a Top Company to Work For, one of the Healthiest Employers in Phoenix, and a Best Place to Work. And, our CEO was recognized as a 2020 40 under 40.

For more information about Metromile, visit www.metromile.com and enterprise.metromile.com

About the role

Metromile recently launched a new B2B business venture, Metromile Enterprise, to license its proprietary AI platform to insurance companies in the US and across the globe. We are looking for a Senior Machine Learning Engineer to join the team developing and launching cutting-edge ML models solving some of the most challenging problems in the personal and commercial insurance industry. This role will work closely with the Data Science and engineering team to deploy and monitor the systems that let our models power business decisions in real time.

If you are excited by the opportunity to explore diverse data sources and collaborate with technical and non-technical team members and stakeholders, we’d love to hear from you!

You will:

Design data models, and data pipelines and implement scalable ETL / ELT processes. Own the deployment of machine learning models into production and monitoring them. Develop backend software for inhouse Data Science platforms and SaaS Products. Work with a small and focused team of experienced data scientists who are passionate about learning and using new technologies Engage in self-driven investigation into new and upcoming technologies/techniques for data management and retrieval.

About you:

3+ years professional experience. Experience with tool sets available in the Cloud (AWS / Azure / GCP etc) used for data storage and data ingestion. Expertise in solutioning and implementing data pipelines. Experience in Kafka or Spark for deploying real time Machine Learning models and solutions. Strong software development fundamentals in Python for building and shipping production data pipelines. Experience with workflow management platform (e.g. Airflow). Experience with storage and processing of sensor data (for example GPS time series) from external systems. Familiarity with data serialization formats such as avro, parquet, protobuf, etc.

Nice to have:

Experience implementing enterprise container platforms like Docker and Kubernetes. Experience with developing Machine Learning Models. Prior experience within the fintech, insurtech, or autonomous vehicle space Experience with unstructured databases (HBase/Cassandra).

What’s in it for you

Competitive salary Stock options for every employee Excellent benefits package (health, dental, vision, 401K) Well-being reimbursement, includes home office equipment Flexible paid vacation program Flexible scheduling/hours Remote work options 13 paid holidays - 2 of which are flex 12 paid weeks of leave for child birth/adoption Annual anniversary gifts (5 yr. - 6 week paid sabbatical) If you got to this point, we hope you're feeling excited about the role. Even if you don't feel that you meet every single requirement, we still encourage you to apply. We're eager to meet people that believe in Metromile’s mission and can contribute to our team in a variety of ways – not just candidates who check all the boxes.

Metromile is committed to building a diverse, inclusive and equitable culture at all levels. We nurture a sense of community by investing in one another’s unique backgrounds and experiences to drive business success and positively influence our services and products.

Metromile is proud to be an equal opportunity employer. We will not discriminate against any applicant or employee on the basis of age, race, color, ethnicity, national origin, citizenship, religion, creed, sex, sexual orientation, gender, gender identity, or expression (including against any individual that is transitioning, has transitioned, or is perceived to be transitioning), marital status or civil partnership/union status, physical or mental disability, medical condition, pregnancy, childbirth, genetic information, military, and veteran status, or any other basis prohibited by applicable federal, state or local law.

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

Posted

This position is unplaced in the org chart

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