ML Engineer, ETA Systems — Hybrid & High-Impact

Lyft; San Francisco (CA); Hybrid; USD 140,800 - 176,000; Full time

Benefits offered by this job

Health insurance

Mental health benefits

Family building benefits

Child care benefits

401(k) plan with company match

Paid time off

Parental leave (18 weeks)?

Commuter benefits

Lyft credits

Lyft Pink membership

Job summary

Lyft is hiring a Machine Learning Engineer for our ETA team in San Francisco. You will build and optimize models that estimate ETAs for ride requests, balancing accuracy with latency to improve matching, pricing estimates, and user experience. The role collaborates with software engineering, data science, and ML teams.

We use AWS, Kubernetes, Go, Spark, Python, and Airflow. You will write production‑quality code that scales to millions of requests daily and participate in code reviews and

Qualifications

• Bachelor's degree in CS or related field or equivalent
• 3+ years of Machine Learning experience
• Nice-to-have: experience with big data processing / distributed data pipelines (Airflow, Spark)
• Ability to work in distributed teams across time zones (NA & EU)

Responsibilities

• Perform data analysis and build proof-of-concept to explore and compare ML and non-ML solutions
• Trade off between model accuracy, productization complexity and runtime performance
• Develop statistical, machine learning, or optimization models
• Write production-quality code that scales to serve millions of requests per day
• Participate in code reviews, design reviews, production on-call support and incident triaging
• Write well-crafted, readable, maintainable code

Skills

ML workflows

Data analysis

Distributed teamwork

Production code quality

Education

Bachelor's degree in Computer Science or related field

Tools

Apache Airflow

Spark

Go

Python

AWS

Kubernetes

Job description

Lyft is hiring a Machine Learning Engineer for our ETA team in San Francisco. You will build and optimize models that estimate ETAs for ride requests, balancing accuracy with latency to improve matching, pricing estimates, and user experience. The role collaborates with software engineering, data science, and ML teams.

We use AWS, Kubernetes, Go, Spark, Python, and Airflow. You will write production‑quality code that scales to millions of requests daily and participate in code reviews and