
About Lyft
The friendly ride-sharing alternative to Uber
Key Highlights
- Headquartered in San Francisco, CA
- Over 100 million rides completed
- $4.9 billion raised in funding
- Acquired PBSC Urban Solutions in 2022
Lyft, headquartered in San Francisco, CA, is a leading ride-sharing company focused on improving transportation experiences in the U.S. and Canada. With over 100 million rides completed and $4.9 billion raised in funding, Lyft aims to provide a more reliable and environmentally friendly alternative ...
🎁 Benefits
Lyft offers a comprehensive benefits package including unlimited paid time off for salaried employees, 15 days PTO for hourly team members, and 18 wee...
🌟 Culture
Lyft fosters a culture focused on reliability and friendliness, positioning itself as a greener alternative to Uber. The company emphasizes local oper...

Machine Learning Engineer • Mid-Level
Lyft • San Francisco - On-Site
Skills & Technologies
Overview
Lyft is seeking a Machine Learning Engineer to develop algorithms that enhance fraud detection and prevention on their platform. You'll work with Python and machine learning frameworks like TensorFlow and Keras in San Francisco. This position requires expertise in data analysis and machine learning systems.
Job Description
Who you are
You have a strong background in machine learning and data analysis, with experience developing and deploying algorithms that solve complex problems. Your expertise in Python and familiarity with frameworks such as TensorFlow and Keras enable you to build reliable ML systems that directly impact business outcomes. You thrive in collaborative environments and are eager to contribute to a team focused on enhancing trust and safety through innovative solutions. You understand the importance of operational excellence and are committed to maintaining high standards in your work.
You possess a deep understanding of machine learning principles and have applied them in real-world scenarios, particularly in fraud detection and prevention. Your analytical mindset allows you to dissect problems and develop effective strategies to address them. You are comfortable working with diverse datasets and can extract meaningful insights that drive decision-making. You are excited about the opportunity to work in a fast-paced environment and are motivated by the challenge of tackling unique problems in the transportation sector.
Desirable
Experience with large-scale data processing and familiarity with cloud platforms is a plus. You may have worked on projects that involve forecasting, mapping, or personalization, showcasing your versatility in applying machine learning across various domains. A passion for continuous learning and staying updated with the latest advancements in AI and machine learning technologies is essential.
What you'll do
As a Machine Learning Engineer at Lyft, you will be responsible for developing and launching algorithms that power the platform's core services. You will focus on enhancing fraud detection and prevention mechanisms, ensuring the integrity of the Lyft platform. Your role will involve collaborating with cross-functional teams to identify opportunities for applying machine learning solutions to complex challenges. You will design experiments, analyze results, and iterate on your models to improve their effectiveness.
You will take ownership of the machine learning systems you develop, ensuring they are robust, scalable, and maintainable. Your contributions will directly impact the team's mission to reduce fraud and enhance user trust. You will also be involved in code reviews and mentoring junior engineers, fostering a culture of learning and excellence within the team.
What we offer
Lyft provides a supportive work environment where you can thrive and grow your career. You will have access to competitive compensation, including a salary range of $140,800 - $176,000, depending on your qualifications and experience. In addition to salary, you may be eligible for equity offerings, bonuses, and comprehensive benefits. We encourage you to apply even if your experience doesn't match every requirement, as we value diverse perspectives and backgrounds. Join us in making transportation better for everyone.
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