Impress employers and recruiters.
Choose from hundreds of resume examples.

Impress employers and recruiters.
Choose from hundreds of resume examples.
Tailor your resume to this ML Software Engineer, Routing role.
Rezi rewrites your resume against Lyft's job description. Free.

Tailor your resume to this ML Software Engineer, Routing role.
Rezi rewrites your resume against Lyft's job description. Free.
Don't guess if your resume is good enough.
See how it scores against the ML Software Engineer, Routing posting at Lyft — free, in seconds.

Don't guess if your resume is good enough.
See how it scores against the ML Software Engineer, Routing posting at Lyft — free, in seconds.
About the Role
Lyft is seeking a Machine Learning Engineer to join their Routing team. This role involves building and maintaining Lyft's system for providing routes for every ride request, processing millions of requests daily with a focus on low latency, high reliability, and accuracy. The ideal candidate is a critical thinker with experience in machine learning workflows, writing reliable code, and solving business problems with data in a dynamic environment.
Responsibilities
- Perform data analysis and build proof-of-concept to explore and compare ML and non-ML solutions
- Make effective tradeoffs between model accuracy, 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
- Write well-crafted, well-tested, readable, maintainable code
Requirements
- B.S., M.S., or Ph.D. in Computer Science or other quantitative fields or related work experience
- 3+ years of Machine Learning experience
- Proficiency in at least one of the SQL languages (MySQL, PostgreSQL, SqlServer, Oracle)
- Ability to work in distributed teams spread across time zones (EST and PST)
Skills
- Machine learning workflows
- Writing reliable code
- Solving business problems using data
- Big data processing
- Distributed data pipelines
- Apache Airflow
- Spark/Flink
- SQL
Location
- Toronto
Work Type
- Hybrid
- In-office (at least 3 days per week)
- Remote (up to 4 weeks per year)
Experience Level
- 3+ years of Machine Learning experience
Education Level
- B.S., M.S., or Ph.D. in Computer Science or other quantitative fields or related work experience
Salary/Compensations
- CAD $118,800 - CAD $148,500
Benefits
- Extended health and dental coverage options
- Life insurance
- Disability benefits
- Mental health benefits
- Family building benefits
- Child care benefits
- Pet benefits
- Lyft funded Health Care Savings Account
- RRSP plan with company match
- Flexible paid time off policy
- 18 weeks of paid time off for new parents
- Subsidized commuter benefits
- Lyft ride credits
About the Company
- Lyft's purpose is to serve and connect, aiming to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.
- Their transport network serves millions of people daily using Lyft cars, bikes, scooters, or on foot.
- Their technology stack runs on AWS, Kubernetes, Go, Python/C++, Apache Airflow, Flink, and Kafka.
- They use AI to improve development productivity, optimize customer support workflows, and enhance operational efficiency.
Equal Opportunity
- 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.