Staff ML Engineer: Personalization & Real-Time Optimization

Doordashusa; San Francisco (CA); Hybrid; USD 137,100 - 201,600; Full time

Benefits offered by this job

401(k) with employer matching

16 weeks of paid parental leave

Comprehensive wellness benefits

Equity grant opportunities

Job summary

Doordashusa is looking for a Staff Machine Learning Engineer in San Francisco to develop large-scale ML systems aimed at personalizing the DashPass Subscriber experience. With over 8 years of experience and proficiency in Python, Java, and C++, the ideal candidate will design and implement innovative solutions impactfully.

This role combines technical expertise with mentorship opportunities, aiming to optimize customer growth through cutting-edge ML techniques while contributing significantly to team development.

Qualifications

• 8+ years of industry experience building production-scale ML systems.
• Proficiency in using AI coding tools in the full software development lifecycle.
• Strong understanding of probability theory, statistics, and machine learning fundamentals.

Responsibilities

• Drive the design and development of large-scale ML/optimization systems.
• Partner closely with cross-functional teams to design experiments and model frameworks.
• Build and deploy 0→1 ML systems to improve subscriber outcomes.

Skills

Machine Learning

Python

Java

C++

Data Science

Statistical Analysis

Education

M.S. or Ph.D. in Computer Science, Machine Learning, Statistics

Tools

TensorFlow

PyTorch

XGBoost

Job description

Doordashusa is looking for a Staff Machine Learning Engineer in San Francisco to develop large-scale ML systems aimed at personalizing the DashPass Subscriber experience. With over 8 years of experience and proficiency in Python, Java, and C++, the ideal candidate will design and implement innovative solutions impactfully.

This role combines technical expertise with mentorship opportunities, aiming to optimize customer growth through cutting-edge ML techniques while contributing significantly to team development.