Lyft Machine Learning Engineer at Lyft to design, develop, and deploy state-of-the-art machine learning systems for real-time applications. Collaborate across teams to leverage ML and data science to impact ride-sharing core business.
Responsibilities
Design, build, and deploy machine learning models for real-time applications, including translating state-of-the-art research into production-ready solutions
Design and implement feature pipelines, model training workflows, and serving infrastructure using Lyft's ML platform
Evaluate ML system performance against business KPIs, run experiments, and drive continuous model improvement
Partner with ML engineers, product managers, data scientists, and software engineers to align ML initiatives with business goals
Leverage data-driven insights to inform and refine ML strategies and solutions
Write production-level code and participate in code reviews to ensure quality and share knowledge across the team
BS/MS in Computer Science, or a related field
2+ years of experience in machine learning modeling or related fields
Experience with deep learning technologies for recommendation systems, including TensorFlow, PyTorch, or similar frameworks
Understanding of statistical concepts such as hypothesis testing, regression analysis, and performance evaluation metrics for machine learning
Experience with translating state-of-the-art ML research into production systems
Proficiency in Python, Golang, or other programming language
Qualification
Proficiency in Python
Required
BS/MS in Computer Science or related field
2+ years of experience in machine learning modeling or related fields
Experience with deep learning technologies for recommendation systems
Understanding of statistical concepts such as hypothesis testing, regression analysis, and performance evaluation metrics
Experience translating state-of-the-art ML research into production systems
Proficiency in Python, Golang, or other programming language
Proven ability to tackle ambiguous problems and deliver solutions at scale
