Backend Engineer, ML, AI and OR Platform

Lyft; Toronto; Hybrid; CAD 108,000 - 135,000; Full time

Job summary

A leading company is seeking a Backend Engineer to join their Machine Learning Platform team. This role involves solving complex problems at scale using machine learning and AI technologies. The ideal candidate should have a solid foundation in software engineering alongside hands-on experience in developing and integrating ML systems. The position offers a collaborative environment with opportunities for growth and flexible working arrangements within a dynamic team.

Benefits

Extended health and dental coverage

Family building benefits

Child care and pet benefits

Health Care Savings Account

RRSP plan for future savings

Flexible paid time off policy

18 weeks paid time off for new parents

Qualifications

• 3+ years of engineering experience in Python, Java, or GO.
• BSc/MSc or relevant work experience.
• Experience in machine learning systems is an advantage.

Responsibilities

• Contribute to the roadmap and architecture based on technology and business needs.
• Write maintainable code and participate in code reviews.
• Proactively resolve ongoing incidents and unblocking team challenges.

Skills

Python

Java

GO

Education

BSc/MSc in Computer Engineering, Computer Science, related field

Tools

Linux

Job description

Backend Engineer, ML, AI and OR Platform

At Lyft, our purpose is to serve and connect. To do this, we start with our own community by creating an open, inclusive, and diverse organization.

With over half a billion rides and counting, Lyft is solving hard problems at scale, leveraging Machine Learning and AI to better serve our customers. The Machine Learning Platform team is seeking a Software Engineer interested in contributing to our platform which supports real-time, online, and offline ML model execution, development, and iteration. You will work with a team of highly motivated Machine Learning and Software Engineers on challenging problems, defining solutions to directly impact systems across the entire business.

If you are interested in hands-on exposure to classical machine learning models, production ML systems at scale, with applications across each facet of the marketplace and business, we are searching for you.

If you are a creative and critical thinker with an interest or experience in machine learning systems, passionate about solving business problems using data and working in a dynamic, creative, and collaborative environment, we are searching for you.

Responsibilities:

• Contribute to the roadmap and architecture based on technology and business needs
• Write well-crafted, well-tested, readable, maintainable code
• Have a good grasp and ability to explain the various tradeoffs made in decisions
• Participate in code reviews to ensure code quality and distribute knowledge
• Build Features from tech specification to positive execution
• Incorporate considerations for business context and failure modes in your work
• Proactively participate in resolving ongoing incidents
• Unblock, support, effectively communicate, and obtain buy-in within your team to achieve results
• Share your knowledge by giving brown bags and tech talks.

Experience:

• BSc/MSc in Computer Engineering, Computer Science, related field or relevant work experience
• 3+ years of engineering experience working in any of these stacks; Python, GO, Java, etc.
• Experience with Linux
• Extended health and dental coverage options, along with life insurance and disability 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.

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 - $135,000. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Range is not inclusive of potential equity offering, bonus or benefits. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.

About the company

Lyft, Inc. develops, markets, and operates a mobile app, offering vehicles for hire, motorized scooters, a bicycle-sharing system, and food delivery.

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