Easter Seals Jobs

At Lyft, our mission is to improve people’s lives with the world’s best transportation. To do this, we start with our own community by creating an open, inclusive, and diverse organization.

Data and Machine Learning are at the heart of Lyft’s products and decision-making. As a member of the Machine Learning Platform team, you will work in a dynamic environment, where we embrace moving quickly to build the world’s best transportation network. Machine learning infra engineers build systems that empower machine learning models to make our products predictive, personalized, and adaptive. We’re looking for passionate, driven engineers to take on some of the most interesting and impactful problems in ridesharing.

As a machine learning platform engineer, you will be developing our central machine learning platform that powers Lyft machine learning and optimization models. You will be working on a wide array of challenges ranging from building the large language model framework, large scale distributed model training, sub millisecond real-time predictions at scale, automating machine learning model lifecycle, implementing model monitoring, enabling reinforcement learning and many more. You will be working in a fast paced environment, tackling a diverse set of problems. They collaborate across transportation, economics, forecasting, mapping, personalization, and adaptive control. We are hiring engineers who can work with modelers across the company and build infrastructure to incorporate the rapid developing needs 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 Machine Learning Engineers, Data Scientists, Software Engineers and Product Managers to develop advanced systems for business and user impact

• Evaluate when to build and when to reuse existing components including open source solutions

• Write production quality code that scales with use.

Experience:

• B.S., M.S. or Ph.D. in Computer Science, related technical field or relevant work experience

• 3+ years of industry or research experience developing ML models or infrastructure

• Passion for building scalable and extensible solutions for machine learning development and productionisation towards short term and long term business and user impact

• Proficiency in Python, Golang, or other programming language

• Excellent communication skills and fluency in English

Benefits:

• Extended health and dental coverage options, along with life insurance and disability benefits

• Mental health benefits

• Family building benefits

• Access to a Health Care Savings Account

• In addition to provincial observed holidays, team members get 15 days paid time off, with an additional day for each year of service

• 4 Floating Holidays each calendar year prorated based off of date of hire

• 10 paid sick days per year regardless of province

• 18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible

Lyft proudly pursues and hires a diverse workforce. 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 now if you wish to make such a request.

This role will be in-office on a hybrid schedule — Team Members will be expected to work in the office 3 days per week on Mondays, Thursdays and a team-specific third day. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid