Machine Learning Engineer, Fulfillment

Lyft

Confirmed live today High trust

Hybrid

Quick summary

Work type: Hybrid
Location: San Francisco, CA
Salary: $140,800–$176,000 / yr
Posted: 70 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $229k

This role $158k

$124k $294k

below market most similar roles pay here above market

This role pays less than 95% of similar roles. Most pay $202,800–$254,750 — the blue band above. At the midpoint, this role pays about $158k versus about $229k for comparable roles.

Based on 240 similar postings.

Employer

About Lyft

Lyft is a transportation network company offering ride-hailing services across the US and Canada.

Lyft currently has 35 open roles on FindRole.

Listed pay typically runs $148,000–$185,000 across 31 roles with salary data.

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View all roles at Lyft

At a glance

TL;DR · Machine Learning Engineer, Fulfillment

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The Machine Learning Engineer, Fulfillment joins the Fulfillment group within the Marketplace team to design, develop, and deploy state-of-the-art machine learning systems. This role involves translating research into production-ready solutions, building feature pipelines, and implementing model training workflows and serving infrastructure. The engineer will evaluate system performance against business KPIs, run experiments, and write production-level code while collaborating with cross-functional partners. Key technical requirements include proficiency in Python or Golang and experience with deep learning frameworks like TensorFlow or PyTorch for recommendation systems. Candidates must understand statistical concepts such as hypothesis testing and regression analysis. The work focuses on the technical problem of determining reliable inventory for rider sessions, matching requests with drivers, and maintaining a distributed state machine to track rides.

What does a Machine Learning Engineer earn in California?

Median $235750 from 200 postings across 34 companies.

See salary data

Skills

Machine Learning Python Golang TensorFlow PyTorch Deep Learning Recommendation Systems Feature Pipelines Model Training Regression Analysis Hypothesis Testing Production Systems

What you'll do

Design, build, and deploy machine learning models for real-time applications.
Translate state-of-the-art research into production-ready machine learning solutions.
Implement feature pipelines, model training workflows, and serving infrastructure.
Evaluate ML system performance against business KPIs and run experiments.
Drive continuous model improvement using data-driven insights.
Write production-level code and participate in peer code reviews.

What we're looking for

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.
Experience with translating state-of-the-art ML research into production systems.
Proficiency in Python, Golang, or other programming languages.
Proven ability to tackle ambiguous problems and deliver solutions at scale.
Strong communication and interpersonal skills for effective cross-functional collaboration.