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ML Software Engineer, ETA

Lyf*** · San Francisco, CA, United States
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San Francisco, CA, United States140,800-176,000 USD/yearlyHybrid
Remuneration
140,800-176,000 USD/yearly
Location
San Francisco, CA, United States
Visa sponsorship
Sponsors visa

Job summary

At Lyf***, 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. We are hiring a Machine Learning Engineer to join our ETA team.

Benefits

Great medical, dental, and vision insurance options with additional programs avaMental healthFamily buildingChild care and pet401(k) plan with company match to help save for your future18 weeks of paid parental leave.Biological, adoptive, and foster parents are all eligibleSubsidized commuterMonthly Lyft credits and complimentary Lyft Pink membershipLyft is an equal opportunity employer committed to an inclusive workplace that fWe also consider qualified applicants with criminal histories consistent with apLyft highly values having employees working in-office to foster a collaborative

Qualifications

  • ETAs play a critical role in matching decisions, pricing estimates and overall user experience.
  • experience and geographic location.
  • Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.

Responsibilities

  • Our team builds and maintains Lyf***'s system responsible for estimating/predicting ETAs for every ride request on our platform.
  • In this role, you will work with incredibly passionate and talented colleagues from software engineering, machine learning and data science on building rideshare experiences that delight millions of riders and drivers.
  • Perform data analysis and build proof-of-concept to explore and compare ML and non-ML solutions
  • Be able to make effective tradeoffs between model accuracy, its productization complexity and runtime performance
  • Develop statistical, machine learning, or optimization models
  • Write production quality code that can scale well to serve millions of requests per day
  • Participate in code reviews, design reviews, production on-call support and incident triaging process.
  • Write well-crafted, well-tested, readable, maintainable code
  • EXPERIENCE:
  • B.
  • S., M.
  • S., or Ph.

Degrees

AssociateBachelorPhD

Work schedule

On-call

Industry

InsurancePublic-sector