Senior Personalization ML Engineer, Consumer

DoorDash; Sunnyvale (CA); On-site; USD 242,800 - 357,000; Full time

Benefits offered by this job

401(k) plan with employer matching

Health, dental, and vision benefits

16 weeks paid parental leave

Flexible paid time off

Job summary

DoorDash is seeking a Senior Staff Machine Learning Engineer to lead the personalization strategy for consumer shopping. In this role, you will leverage robust data and machine learning infrastructure to create relevant and delightful search experiences across different business sectors.

The ideal candidate will have substantial experience in developing machine learning models and leading technical projects. You will be responsible for guiding teams and implementing innovative solutions that enhance our recommendation system.

Qualifications

• 10+ years of industry experience developing machine learning models with business impact and shipping ML solutions to production.
• Proficiency in using AI coding tools (e.g., Claude Code) throughout the software development lifecycle.
• Deep expertise in deep learning and fine-tuning; hands-on experience optimizing LLM systems.

Responsibilities

• Drive the engineering vision and strategy for an organization of 150+.
• Grow and mentor impactful business-focused product engineering teams.
• Partner with Business and Product teams to transform DoorDash's commerce approach.

Skills

Machine learning models

Deep learning

AI coding tools

Technical leadership

Cross-functional collaboration

Education

B.S. or M.S. in Computer Science or equivalent

Job description

DoorDash is seeking a Senior Staff Machine Learning Engineer to lead the personalization strategy for consumer shopping. In this role, you will leverage robust data and machine learning infrastructure to create relevant and delightful search experiences across different business sectors.

The ideal candidate will have substantial experience in developing machine learning models and leading technical projects. You will be responsible for guiding teams and implementing innovative solutions that enhance our recommendation system.