Staff Machine Learning Engineer, Lyft
$172-215k
More information about location
3+ days a week in office
Ride sharing company
Posted today
Ride sharing company
1001+ employees
Posted today
$172-215k
More information about location
3+ days a week in office
1001+ employees
Company mission
To improve people’s lives with the world’s best transportation.
Role
Who you are
- 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
- B.S., M.S. or Ph.D. in Computer Science or related technical field or relevant work experience
- 8+ years (or Ph.D. with 6+ years) of experience in machine learning, data science, or related fields, with at least 3 years in a senior or staff engineering role
- Deep understanding of supervised/unsupervised learning, reinforcement learning, and advanced optimization techniques
- Deep knowledge of ML libraries like scikit-learn, Tensorflow, PyTorch, Keras, etc
- Experience with distributed computing frameworks like Spark, Hadoop
- Strong knowledge of cloud platforms (e.g., AWS, GCP) and containerization tools (e.g., Docker, Kubernetes)
- Proven ability to quickly and effectively turn research ML papers into working code
- Practical knowledge of how to build efficient end-to-end ML workflows
- Proven ability to tackle ambiguous problems and deliver solutions at scale
- Strong communication and interpersonal skills for effective cross-functional collaboration
- "Engineer at heart" with a high degree of comfort in designing software systems and producing high-quality code
What the job involves
- We are seeking a Staff Machine Learning Engineer to lead the design, development, and deployment of state-of-the-art machine learning systems.
- This role requires a strategic thinker who can balance high-level system architecture with hands-on technical implementation.
- You will collaborate across teams to shape the future of ride-sharing by leveraging AI, Machine learning and Data science
- Model Development: Design, build, train, and deploy machine learning models for real-time applications
- System Design: Architect scalable, reliable, and maintainable machine learning pipelines, integrating seamlessly with existing backend systems
- Collaboration: Work closely with machine learning engineers, product managers, data scientists, and software engineers to align machine learning initiatives with business goals
- Innovation: Stay ahead of the curve by exploring new algorithms, technologies, and frameworks to solve complex problems and introduce use cases for the team. Critically evaluate problems across business areas
- Data-Driven Decision Making: Utilize data-driven insights to inform and refine machine learning strategies and solutions
- Mentorship: Provide technical leadership, mentor engineers, and foster a culture of learning and collaboration
- Code Quality: Write production-level code to convert your ML models into working pipelines and participate in code reviews to ensure code quality and distribute knowledge
Our take
Lyft has aimed for consistent growth, making sure to pitch itself as a more reliable and friendly ride-sharing option than its main competitor, Uber. Uber has a greater market share and operates globally, but Lyft hopes to compete by its focus on ride-sharing over Uber's more diversified business approach and as a more rider-friendly and greener alternative to Uber.
Operating only in the USA and Canada, Lyft is in a position of being less affected by global events than Uber but also more vulnerable to local conditions. As an example, while it doesn't face the regulatory hurdles around employment rights that Uber does, it is unable to balance out the cost of the unusually expensive US auto insurance across its operations.
In 2022, Lyft acquired PBSC Urban Solutions, a bike-share equipment and technology supplier, allowing Lyft to compete in new verticals and reaffirming its commitment to green transportation. It has also trialed and launched Lyft Assisted, where drivers help passengers from their door into the car to get to medical appointments. These developments chime well with Lyft's unique selling point as a friendlier and more environmentally aware ride-sharing app.
Steph
Company Specialist at Welcome to the Jungle
Insights
Company
Funding (last 2 of 14 rounds)
Jun 2018
$600m
LATE VC
Mar 2018
$200m
LATE VC
Total funding: $4.9bn
Company benefits
- Great medical, dental, and vision insurance options
- Mental health benefits
- In addition to 12 observed holidays, salaried team members have unlimited paid time off, hourly team members have 15 days paid time off
- 401(k) plan to help save for your future
- 18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible
- Pre-tax commuter benefits
- Lyft Pink - Lyft team members get an exclusive opportunity to test new benefits of our Ridership Program
- Family building benefits
- Lyft Pink - Lyft team members get an exclusive opportunity to test new benefits of our Ridership Program
Company HQ
China Basin, San Francisco, CA
Articles
Leadership
John Zimmer
(Co-Founder)Originally an Analyst at Lehman Brothers, Zimmer then founded Zimride which was a private ridesharing company that pivoted into Lyft.
Logan Green
(Co-Founder)Founded Zimride, a private ridesharing company which later pivoted into Lyft.
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