Staff Machine Learning Engineer, Personalization

DoorDash, Inc.; San Francisco, Sunnyvale (CA, CA); Hybrid; USD 204,000 - 299,000; Full time

Benefits offered by this job

Equity grants

401(k) matching

Parental leave 16 weeks

Wellness benefits

Job summary

DoorDash seeks an experienced Staff Machine Learning Engineer to design, implement, and validate production ML improvements for growth and personalization in grocery and retail delivery.

You will leverage robust data pipelines and ML infrastructure to enhance consumer search experiences and mentor a multi-disciplinary team in a hybrid work setting.

Qualifications

• 8+ years of industry experience developing ML models with business impact.
• Proficiency with AI coding tools in the full software development lifecycle.
• M.S. or PhD in Statistics, Computer Science, Math, OR, Physics, Economics, or related field.
• Expertise in applied ML for Causal Inference and Recommendation Systems (classical and DL).
• Familiarity with explore/exploit/MAB algorithms and LLMs is a plus.
• Strong Python ML stack experience with PyTorch or TensorFlow.

Responsibilities

• Develop production ML solutions to build a world class personalized shopping experience.
• Partner with engineering and product leaders to shape the ML-driven roadmap.
• Mentor junior team members and lead cross-functional pods for impact.

Skills

Python programming

ML model debugging

Communication

Education

M.S. or PhD in a quantitative field

Tools

PyTorch

TensorFlow

Job description

About the Team

Come help us build the world's most reliable on-demand, logistics engine for last-mile retail delivery! We're looking for an experienced machine learning engineer to help us develop modern growth and personalization models that power DoorDash's growing retail and grocery business.

About the Role

We’re looking for a passionate Applied Machine Learning expert to join our team. As a Staff Machine Learning Engineer, you’ll be conceptualizing, designing, implementing, and validating algorithmic improvements to the growth and personalization experiences at the heart of our fast-growing grocery and retail delivery business. You will use our robust data and machine learning infrastructure to implement new ML solutions to make the consumer search experience more relevant, seamless, and delightful across grocery, convenience, and many other retail categories. You will demonstrate a strong command of production level machine learning, experience with solving end‑user problems, and collaborate well with multi-disciplinary teams. You will report into the engineering manager on our Personalization team.

We expect this role to be hybrid with some time in office and some time remote (#LI-Hybrid).

Responsibilities

• Develop production machine learning solutions to build a world class personalized shopping experience for a diverse and expanding retail space
• Partner with engineering and product leaders to help shape the product roadmap applying ML
• Mentor junior team members, and lead cross functional pods to create collective impact

You can find out more on our ML blog here.

Qualifications

• 8+ 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, Codex, Cursor) in the full software development lifecycle, including designing, generating code, testing, monitoring and releasing software
• M.S., or PhD. in Statistics, Computer Science, Math, Operations Research, Physics, Economics, or other quantitative field
• Expertise in applied ML for Causal Inference and Recommendation Systems - both classical and deep learning based.
• Additional familiarity with explore/exploit/MAB algorithms & LLMs is a plus.
• Machine learning background in Python; experience with PyTorch or TensorFlow preferred.
• Ability to communicate technical details to nontechnical stakeholders.
• You keep the mission in mind, take ideas and help them grow using data and rigorous testing, show evidence of progress and then double down; desire for impact with a growth-minded and collaborative mindset.

Data Retention, Privacy & Bias Audit

Data collected during this process is retained in accordance with our Candidate Privacy Policy and applicable state laws. In compliance with New York City Local Law144, the independent bias audit summary for Gem is publicly available for review at our Careers Page.

Notice to Applicants

For Jobs Located in NYC or Remote Jobs Associated With Office in NYC Only. We use Covey as part of our hiring and/or promotional process for jobs in NYC and certain features may qualify it as an AEDT in NYC. As part of the hiring and/or promotion process, we provide Covey with job requirements and candidate submitted applications. We began using Covey Scout for Inbound from August 21, 2023, through December 21, 2023, and resumed using Covey Scout for Inbound again on June 29, 2024. The Covey tool has been reviewed by an independent auditor. Results of the audit may be viewed here: Covey.

Compensation

The successful candidate’s starting pay will fall within the pay range listed below and is determined based on job‑related factors including, but not limited to, skills, experience, qualifications, work location, and market conditions. Base salary is localized according to an employee’s work location. Ranges are market‑dependent and may be modified in the future. In addition to base salary, the compensation for this role includes opportunities for equity grants.

DoorDash cares about you and your overall well‑being. That’s why we offer a comprehensive benefits package to all regular employees, which includes a 401(k) plan with employer matching, 16 weeks of paid parental leave, wellness benefits, commuter benefits match, paid time off and paid sick leave in compliance with applicable laws (e.g. Colorado Healthy Families and Workplaces Act). DoorDash also offers medical, dental, and vision benefits, 11 paid holidays, disability and basic life insurance, family‑forming assistance, and a mental health program, among others.

To learn more about our benefits, visit our careers page here.

See below for paid time off details: For salaried roles: flexible paid time off/vacation, plus 80 hours of paid sick time per year. For hourly roles: vacation accrued at about 1 hour for every 25.97 hours worked (e.g. about 6.7 hours/month if working 40 hours/week; about 3.4 hours/month if working 20 hours/week), and paid sick time accrued at 1 hour for every 30 hours worked (e.g. about 5.8 hours/month if working 40 hours/week; about 2.9 hours/month if working 20 hours/week). The national base pay range for this position within the United States, including Illinois and Colorado. $203,500 - $299,300 USD

About DoorDash

At DoorDash, our mission to empower local economies shapes how our team members move quickly, learn, and reiterate in order to make impactful decisions that display empathy for our range of users—from Dashers to merchant partners to consumers. We are a technology and logistics company that started by enabling door‑to‑door delivery, and we are looking for team members who can help us go from a company that is known as the place you order food to a company that people turn to for any and all goods. DoorDash is growing rapidly and changing constantly, which gives our team members the opportunity to share their uni.