Software Engineer, Machine Learning (All Levels / All Teams)

DoorDash USA

Sunnyvale, San Francisco, Seattle, New York (CA, CA, WA, NY)

Hybrid

USD 137,000 - 299,000

Full time

3 days ago
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Benefits offered by this job

401(k) matching
Paid parental leave
Wellness benefits
Commuter benefits
Paid time off
Health insurance
Dental & vision benefits
Disability & life insurance

Job summary

DoorDash is hiring Software Engineer, Machine Learning to design, implement, and validate ML solutions that power our catalog system and product knowledge graph. This role spans end-to-end ML lifecycle and requires collaboration with multiple teams in Sunnyvale, San Francisco, Seattle, and New York.

You’ll build scalable ML models, pipelines, and data solutions to improve ads efficiency and platform revenue while working with production infrastructure and a strong ML stack.

Qualifications

  • M.S. or PhD in a technical field such as CS, math, stats, physics, or equivalent.
  • 3+ years ML industry experience with strong fundamentals.
  • Experience with data/feature pipelines at scale and ML systems in production.

Responsibilities

  • Develop advanced ML models to improve ads efficiency and quality.
  • Design optimization algorithms for budget pacing and automated bidding.
  • Establish a data-driven framework to understand bid density and market competitiveness.
  • Develop data solutions like embeddings and consumer profiles.
  • Own end-to-end ML lifecycle from ideation to deployment and monitoring.
  • Extend ML infra to support Ads data applications and experimentation.

Skills

ML model development
Pyspark & Snowflake SQL
PyTorch / Keras / scikit-learn
Production ML systems

Education

M.S. in a technical field (CS, math, stats, physics)

Tools

PyTorch
Keras
LightGBM
scikit-learn
Spark ML
PySpark
Snowflake SQL

Job description

Software Engineer, Machine Learning (All Levels / All Teams)

Sunnyvale, CA; San Francisco, CA; Seattle, WA; New York, NY

About the Role

DoorDash is building the world's most reliable on-demand, logistics engine for delivery. We are continuing to grow rapidly and expanding our Engineering offices globally! We are looking for Software Engineers, Machine Learning to build and maintain a large scale 24x7 global infrastructure system that powers DoorDash's 3-sided marketplace of Consumers, Merchants and Dashers.

As a Software Engineer, Machine Learning, you’ll be conceptualizing, designing, implementing, and validating algorithmic improvements to the catalog system and our product knowledge graph 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 our product knowledge graph accurate, standardized, semantically rich, easily discoverable, and extensible. We’re looking for someone with a command of production-level machine learning and experience with solving end-user problems who enjoys collaborating with multi-disciplinary teams.

This role is hybrid with some in-office time expected and will report to an Engineering Manager.

You're excited about this opportunity because you will...

  • Develop advanced machine learning models to improve ads efficiency and quality.
  • Design and build optimization algorithms for budget pacing and automated bidding to achieve various advertising goals.
  • Establish a data-driven framework to understand how the bid density and market competitiveness would affect advertising value and platform revenue.
  • Develop new data solutions (eg. embeddings and consumer profiles) to target the relevant audience.
  • Be responsible for the end-to-end ML lifecycle, including ideation, offline model training, online shadowing/deployment, experimentation, and post-launch monitoring/measurement.
  • Build and extend the current data/ML infrastructure to empower Ads data applications including data analysis, ML modeling, and experimentation.
  • Scale our systems and services to fuel the growth of our business.
We're excited about you because you have...
  • M.S., or PhD. in a technical field such as computer science, mathematics, statistics, physics or equivalent.
  • 3+ years ML industry experience with a solid understanding of machine learning algorithms and fundamentals.
  • Experience building data/feature engineering pipelines at scale using Pyspark and Snowflake SQL.
  • Experience with building machine learning systems in production by using frameworks such as PyTorch, Keras, lightgbm, scikit-learn, Spark ML, or related.
  • Experiences in any of the following areas are preferred but not required:
  • Online advertising
  • Search relevance & ranking
  • Recommendation system

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. Talk to your recruiter for more information.

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 ranges for this position within the United States, including Illinois and Colorado.

I4

$137,100 - $201,600 USD

I5

$167,800 - $246,800 USD

I6

$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. DoorDash is growing rapidly and changing constantly, which gives our team members the opportunity to share their unique perspectives, solve new challenges, and own their careers. We're committed to supporting employees’ happiness, healthiness, and overall well-being by providing comprehensive benefits and perks including premium healthcare, wellness expense reimbursement, paid parental leave and more.

Our Commitment to Diversity and Inclusion

We’re committed to growing and empowering a more inclusive community within our company, industry, and cities. That’s why we hire and cultivate diverse teams of people from all backgrounds, experiences, and perspectives. We believe that true innovation happens when everyone has room at the table and the tools, resources, and opportunity to excel.

Statement of Non-Discrimination: In keeping with our beliefs and goals, no employee or applicant will face discrimination or harassment based on: race, color, ancestry, national origin, religion, age, gender, marital/domestic partner status, sexual orientation, gender identity or expression, disability status, or veteran status. Above and beyond discrimination and harassment based on “protected categories,” we also strive to prevent other subtler forms of inappropriate behavior (i.e., stereotyping) from ever gaining a foothold in our office. Whether blatant or hidden, barriers to success have no place at DoorDash. We value a diverse workforce – people who identify as women, non-binary or gender non-conforming, LGBTQIA+, American Indian or Native Alaskan, Black or African American, Hispanic or Latinx, Native Hawaiian or Other Pacific Islander, differently-abled, caretakers and parents, and veterans are strongly encouraged to apply. Thank you to the Level Playing Field Institute for this statement of non-discrimination.

Pursuant to the San Francisco Fair Chance Ordinance, Los Angeles Fair Chance Initiative for Hiring Ordinance, and any other state or local hiring regulations, we will consider for employment any qualified applicant, including those with arrest and conviction records, in a manner consistent with the applicable regulation.

If you need any accommodations, please inform your recruiting contact upon initial connection.

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