Machine Learning Engineer, Recommendations at Lyft, Inc.

Toronto, Ontario, Canada -

Full Time

Start Date

Immediate

Expiry Date

19 Apr, 26

Salary

148500.0

Posted On

19 Jan, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Data Analysis, Statistical Modeling, Optimization Models, Python, Golang, Supervised Learning, Forecasting, Recommendation Systems, Reinforcement Learning, Multi-Armed Bandits, Communication Skills, Critical Thinking, Collaboration, Problem Solving

Industry

Ground Passenger Transportation

Description

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. With over half a billion rides and counting, Lyft is solving hard problems in a rapidly growing domain with a lot of data and creative solutions in Marketplace, Mapping, Fraud, Trust & Safety, Growth and beyond. While traditional approaches to optimization and problem decomposition are sufficient to disrupt transportation, building next-generation platform for low-cost, ultra-immersive transportation to improve people’s lives warrants modern ML utilizing peta-byte scale data. Our highly motivated Machine Learning Engineers work on these challenging problems and define solutions to directly impact various aspects of our core business. If you are a critical thinker with experience in machine learning workflows, passionate about solving business problems using data and working in a dynamic, creative, and collaborative environment, we are searching for you. As a machine learning engineer, you will be developing and launching the algorithms that power the platform’s core services and impactful products. Compared to similarly-sized technology companies, the set of problems that we tackle is incredibly diverse. They cut across transportation, economics, forecasting, mapping, safety, personalization, and adaptive control. We are hiring motivated experts in each of these fields. We’re looking for someone who is passionate about solving problems with data, building reliable ML systems, and is excited about working in a fast-paced, innovative, and collegial environment. Responsibilities: Partner with Engineers, Data Scientists, Product Managers, and Business Partners to apply machine learning for business and user impact Perform data analysis and build proof-of-concept to explore and propose ML solutions to both new and existing problems Develop statistical, machine learning, or optimization models Write production quality code to launch machine learning models at scale Evaluate machine learning systems against business goal Experience: B.S., M.S., or Ph.D. in Computer Science or other quantitative fields or related work experience 3+ years of Machine Learning experience Passion for building impactful machine learning models leveraging expertise in one or multiple fields. Proficiency in Python, Golang, or other programming language Excellent communication skills and fluency in English Strong understanding of Machine Learning methodologies, including supervised learning, forecasting, recommendation systems, reinforcement learning, and multi-armed bandits Benefits: Extended health and dental coverage options, along with life insurance and disability benefits Mental health benefits Family building benefits Child care and pet benefits Access to a Lyft funded Health Care Savings Account RRSP plan to help save for your future In addition to provincial observed holidays, salaried team members are covered under Lyft's flexible paid time off policy. The policy allows team members to take off as much time as they need (with manager approval). Hourly team members get 15 days paid time off, with an additional day for each year of service Lyft is proud to support new parents with 18 weeks of paid time off, designed as a top-up plan to complement provincial programs. Biological, adoptive, and foster parents are all eligible. Subsidized commuter benefits 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. 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 — Team Members will be expected to work in the office at least 3 days per week, including 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 The expected base pay range for this position in the Toronto area is CAD $118,800 - CAD $148,500, not inclusive of potential equity offering, bonus or benefits. Salary ranges are dependent on a variety of factors, including qualifications, 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. Lyft may use artificial intelligence to screen applicants, however, Lyft employees make the ultimate selection and hiring decisions. This job fills an existing vacancy.

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Responsibilities

The Machine Learning Engineer will partner with various teams to apply machine learning for business impact and develop algorithms for core services. They will also perform data analysis and build proof-of-concept models to explore ML solutions.