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职位Lyft

Software Engineer, AI Entries

Lyft

Software Engineer, AI Entries

Lyft

Toronto, Canada

·

On-site

·

Full-time

·

1mo ago

必备技能

Python

Go

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.

Lyft is looking for software engineers from a scope of disciplines. We are growing our team with people who want to build, improve and incorporate technologies that make the lives of our community more enriched. As an engineer at Lyft, you'll collaborate with teams like product, data science, analytics, and operations on code that empower us to iterate quickly, while focusing on delighting our passengers and drivers.

About the Role:

The Applied AI team is looking for a Backend Engineer to join the AI Entries team. You will build the foundational infrastructure that connects Lyft to emerging AI ecosystems and devices and architect the APIs and orchestration layers that allow third-party agents and multimodal interfaces to interact with Lyft. By building these robust integration, you will help make Lyft available where our riders are.

Responsibilities:

  • Drive high-impact projects and innovate new solutions to provide the best user experience.

  • Lead large features from idea to positive execution and launch

  • Write well-crafted, well-tested, readable, maintainable code

  • Participate in code reviews to ensure code quality and distribute knowledge

  • Participate in our teams on call rotation. Identify, triage, debug and resolve issues/bugs across our various applications and platforms

  • Have the ability to explain the various trade offs made in decisions

  • Manage project priorities, deadlines, and deliverables.

Experience:

  • BS/MS or equivalent in Computer Engineering, Computer Science, or related field or equivalent practical experience.

  • 2+ years of software engineering/production infrastructure industry experience.

  • Experience with Python and Go.

  • Proficiency in object-oriented programming.

  • Experience working with data structures or algorithms.

  • Ability to work with a low-ego, highly collaborative, and cross-functional team.

  • Bonus points: Experience with LLM orchestration (Lang Chain, etc.), Vector Databases, or building APIs for conversational agents.

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 with company match 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 and Lyft ride credits

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 $108,000 - CAD $135,000, 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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关于Lyft

Lyft

Lyft

Public

Lyft, Inc. is an American company offering ride-hailing services, motorized scooters, and bicycle-sharing systems in the United States and Canada, and, via its Free Now mobile app, Europe. Lyft is the second-largest ridesharing company in the United States after Uber.

1,001-5,000

员工数

San Francisco

总部位置

$3.2B

企业估值

评价

3.9

10条评价

工作生活平衡

3.8

薪酬

3.2

企业文化

4.2

职业发展

3.5

管理层

3.7

72%

推荐给朋友

优点

Flexible hours/schedule

Great team culture

Good work-life balance

缺点

Long hours

Fast-paced work environment

Pay could be better

薪资范围

52个数据点

Junior/L3

Mid/L4

Senior/L5

Junior/L3 · Analyst

1份报告

$146,004

年薪总额

基本工资

$126,960

股票

-

奖金

-

$146,004

$146,004

面试经验

2次面试

难度

3.0

/ 5

时长

14-28周

录用率

50%

面试流程

1

Application Review

2

Recruiter Screen

3

Technical Assessment

4

Technical Interview

5

Onsite/Virtual Interviews

6

Offer

常见问题

Coding/Algorithm

System Design

Behavioral/STAR

Technical Knowledge