Senior Software Engineer, Machine Learning
San Francisco, CA; New York, NY; Seattle, WA
- Pay
USD 167,800–246,800/yearAnnual period assumed — pay source
The national base pay range for this position within the United States, including Illinois and Colorado. $167,800—$246,800 USD About DoorDash
Read the full posting- Work setting
Hybrid — work setting source
As a Senior 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. We expect Senior Engineers to be able to own projects end-to-end and mentor their junior and mid level peers. 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...
Read the full posting- Employment
- Not stated
What you’ll work on
Full postingAs a Senior 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.
This role is hybrid with some in-office time expected and will report to an Engineering Manager.
Develop advanced machine learning models for the catalog and product knowledge graph
Own the end-to-end ML lifecycle, from ideation through post-launch monitoring
Scale systems and services to support business growth
Mentor junior and mid-level engineers
From the employer’s posting
As a Senior 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. We expect Senior Engineers to be able to own projects end-to-end and mentor their junior and mid level peers.
This role is hybrid with some in-office time expected and will report to an Engineering Manager.
Develop advanced machine learning models to improve core parts of your teams scope.
Be responsible for the end-to-end ML lifecycle, including ideation, offline model training, online shadowing/deployment, experimentation, and post-launch monitoring/measurement.
Scale our systems and services to fuel the growth of our business.
mentor their junior and mid level peers
Education & alternatives
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. - 5+ years ML industry experience with a solid understanding of machine learning algorithms and fundamentals.
Tools in this posting
- SQL
- Snowflake
- Keras
- LightGBM
- PySpark
- PyTorch
- scikit-learn
Source — Tool mentions in context
- 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 - 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.
- 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. Compensation
About DoorDash USA
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.
In the employer’s words · Read in context
Posting record
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- Live
- First seen by us
- Oct 14, 2026 · 16 days ago
- Recorded sightings
- 109
- Last seen by us
- Oct 29, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
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Job description
About the Role
As a Senior 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. We expect Senior Engineers to be able to own projects end-to-end and mentor their junior and mid level peers.
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 core parts of your teams scope.
- Be responsible for the end-to-end ML lifecycle, including ideation, offline model training, online shadowing/deployment, experimentation, and post-launch monitoring/measurement.
- Work on creating novel ML & AI solutions that push both our business and the industry forward.
- Scale our systems and services to fuel the growth of our business.
- Completely disrupt logistics by tackling bleeding-edge, technical problems
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.
- 5+ years ML industry experience with a solid understanding of machine learning algorithms and fundamentals.
- 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
- 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.
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).
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 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.
Notice to Applicants for Jobs Located in NYC or Remote Jobs Associated With Office in NYC Only
We used 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 provided Covey with job requirements and candidate submitted applications. We began using Covey Scout for Inbound from August 21, 2023, through December 21, 2023. We resumed using Covey Scout for Inbound again on June 29, 2024, and ceased using Covey Scout for Inbound on April 30, 2026.
The Covey tool has been reviewed by an independent auditor. Results of the audit may be viewed here: https://getcovey.com/nyc-local-law-144.
Beware of recruitment scams: DoorDash, Deliveroo, and Wolt will never ask you to pay money or share sensitive financial information during hiring — learn more about our legitimate recruiting process at Recruitment Scam Awareness - DoorDash .
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
The national base pay range for this position within the United States, including Illinois and Colorado. $167,800—$246,800 USD About DoorDash
- Location & working pattern
San Francisco, CA; New York, NY; Seattle, WA
As a Senior 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. We expect Senior Engineers to be able to own projects end-to-end and mentor their junior and mid level peers. 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...
More source context
If you need any accommodations, please inform your recruiting contact upon initial connection. Notice to Applicants for Jobs Located in NYC or Remote Jobs Associated With Office in NYC Only We used 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 provided Covey with job requirements and candidate submitted applications. We began using Covey Scout for Inbound from August 21, 2023, through December 21, 2023. We resumed using Covey Scout for Inbound again on June 29, 2024, and ceased using Covey Scout for Inbound on April 30, 2026.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
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