{"id":65902,"url":"https://alion.io/job/doordash-staff-machine-learning-engineer-fulfillment-planning","title":"Staff Machine Learning Engineer, Fulfillment Planning","company":{"id":3685,"name":"DoorDash","domain":"doordash.com","url":"https://alion.io/company/doordash-usa","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":{"grade":"B","score":81,"open_postings":79,"ghost_share":0,"stale_share":0.557,"repost_share":0.013,"time_to_fill_p50_days":66,"computed_at":"2026-10-19T05:45:15Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"staff","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["San Francisco, United States","Sunnyvale, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":6,"max":25,"currency":"PEN","period":"hour","gross":null,"usd_annual":14000},"salary_estimate":null,"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":true,"technologies":[{"name":"Edge AI","optional":false},{"name":"Knowledge Distillation","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"Model Distillation","optional":false},{"name":"Platform Engineering","optional":false},{"name":"Python","optional":false}],"status":"live","first_seen_at":"2026-05-27T23:47:57Z","employer_posted_date":"2026-10-12","last_verified_at":"2026-10-19T17:48:09Z","board_verified":true,"closed_at":null,"days_open":144,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":144},"description":"About the Team\nThe Fulfillment Planning team builds the intelligence that powers DoorDash’s logistics network. We optimize how deliveries are planned and executed across the full delivery lifecycle, improving customer experience, merchant outcomes, Dasher efficiency, and DoorDash profitability. Our mission is to improve fulfillment quality while reducing fulfillment cost. We do this by applying machine learning, optimization, and systems engineering to the core decisions behind assignment, routing, batching, timing, and fulfillment estimation.\nThe team works on some of DoorDash’s most important logistics systems, including:\nThe core assignment engine that matches deliveries with Dashers in real time.\nReal-time ETA and fulfillment estimation systems for consumers, Dashers, and merchants across diverse geographies and all business lines.\nAssignment and planning algorithms for specialized delivery types, including grocery, retail, parcel, and catering.\nML models and optimization algorithms that shape demand, improve service quality, and reduce cost.\nTier-0 logistics services that require high reliability, low latency, and strong operational discipline.\nThe team also builds reusable ML systems and modeling patterns that scale across DoorDash’s logistics ecosystem. This role will help define the technical direction and best practices for logistics ML at DoorDash.\nAbout the Role\nWe’re looking for a Staff Machine Learning Engineer to lead the design, development, and deployment of large-scale production ML systems that drive real-time decisioning across DoorDash’s fulfillment ecosystem.\nYou will start by owning ML systems for assignment and fulfillment estimation, partnering closely with Product, Data Science, Engineering, and Platform teams to improve delivery quality, cost, and efficiency. Over time, you may also contribute to adjacent areas such as batching, fulfillment execution, demand shaping, and logistics optimization across DoorDash’s business lines.\nThis is a high-impact individual contributor role for someone who enjoys building 0→1 ML systems, operating at Staff-level scope, and influencing technical direction across multiple teams. You will define architectures, set modeling and deployment standards, mentor other engineers, and help shape how DoorDash applies machine learning to logistics at scale.\nYou’re excited about this opportunity because you will…\nOwn and build foundational ML systems that directly impact delivery quality, cost, and overall logistics efficiency across DoorDash.\nWork on challenging, real-world machine learning problems, including real-time assignment, routing, and fulfillment estimation.\nLead 0→1 ML initiatives, defining how machine learning and optimization are applied across fulfillment products.\nInfluence architecture, strategy, and execution for a Tier-0 service critical to DoorDash’s logistics platform.\nCollaborate closely with Product, Data Science, and Platform Engineering in a highly cross-functional environment.\nEstablish best practices for model development, deployment, monitoring, retraining, and governance.\nDefine and lead DoorDash’s cutting-edge AI vision for logistics: an LLM-inspired foundation model for intelligence across logistics\nMentor other engineers and raise the technical bar for logistics ML across the organization.\nWe’re excited about you because…\nYou have 8+ years of industry experience building and deploying production-scale machine learning systems.\nYou have strong machine learning fundamentals and know how to apply them to large-scale production systems.\nYou are fluent in Python\nYou have hands-on experience with modern ML frameworks, especially deep learning frameworks.\nYou have designed, launched, and operated mission-critical ML models or systems in production, including monitoring, retraining, reliability, and governance.\nYou can lead complex technical projects end to end and influence stakeholders across multiple teams or organizations.\nYou communicate clearly with both technical and non-technical audiences.\nYou are comfortable operating in ambiguous problem spaces and turning 0→1 ideas into production systems.\nYou have built or shipped large-scale ML models for recommendation, ads, marketplace, logistics, or other domains.\nYou have experience with knowledge distillation from large teacher models into efficient production models.\nNotice Regarding Use of AI and Automated Tools: To streamline our hiring process, DoorDash utilizes an automated recruitment tool called Gem.\nHow it works: Gem assists our recruiting team by evaluating job related qualifications and characteristics in connection with hiring. The tool is designed and used to support - rather than replace - human decision-making; trained personnel make final decisions with meaningful human review and oversight, and DoorDash does not use Gem or other AI-enabled tool in a manner that has the effect of subjecting applicants or employees to discrimination based on any protected characteristic or proxy or for engaging in any protected activity under applicable law.\nData 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 Law 144, the independent bias audit summary for Gem is publicly available for review at our Careers Page. \nNotice to Applicants for Jobs Located in NYC or Remote Jobs Associated With Office in NYC Only\nWe 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.\nThe Covey tool has been reviewed by an independent auditor. Results of the audit may be viewed here: Covey\nCompensation\n\nThe 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.\nIn addition to base salary, the compensation for this role includes opportunities for equity grants. Talk to your recruiter for more information.\nDoorDash 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.\nTo learn more about our benefits, visit our careers page here.\nSee below for paid time off details:\nFor salaried roles: flexible paid time off/vacation, plus 80 hours of paid sick time per year.\n 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).\nThe national base pay ranges for this position within the United States, including Illinois and Colorado.\nI4\n$137,100—$201,600 USD\nI5\n$167,800—$246,800 USD\nI6\n$203,500—$299,300 USD\nAbout DoorDash\nAt 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.\nDoorDash 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.\nOur Commitment to Diversity and Inclusion\nWe’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.\nStatement 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.\nPursuant 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.\nIf you need any accommodations, please inform your recruiting contact upon initial connection.\n\nNotice to Applicants for Jobs Located in NYC or Remote Jobs Associated With Office in NYC Only\nWe 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.\nThe Covey tool has been reviewed by an independent auditor. Results of the audit may be viewed here: https://getcovey.com/nyc-local-law-144.\nBeware 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.","description_format":"text","description_chars":11528,"description_truncated":false,"requirements":{"experience_years_min":8,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"phd","optional":false},"security_clearance":false,"languages":[]},"benefits":["Equity","Life insurance","Parental leave"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Delivery","Marketplaces"],"lifecycle":[{"event":"open","at":"2026-05-27T23:47:57Z"}],"visa":[{"country":"US","licensed_sponsor":true,"evidence":"H-1B filings in 12 months: 504 · green card filings: 110","filings_12m":504,"filings_prev_12m":584,"green_card_filings_12m":110,"median_offered_wage_usd":172500,"route":null,"cap_exempt":false,"checked_at":"2026-10-15T11:24:14+00:00","sources":["US Department of Labor: LCA disclosure data (H-1B, H-1B1, E-3)","US Department of Labor: PERM disclosure data (green cards)"],"filings_for_role_12m":312}],"liveness":{"score":13,"band":"cold","label":"Long shot","p_open":1,"p_active":0.448,"p_room":0.28,"age_days":144,"expected_fill_days":66,"reasons":["conf:3","stale_co","velocity","win:tail","crowd:brand"],"computed_at":"2026-10-19T05:45:15Z"},"pay":{"stated_usd_annual":14000,"is_top_pay":false},"html_url":"https://alion.io/job/doordash-staff-machine-learning-engineer-fulfillment-planning","json_url":"https://alion.io/job/doordash-staff-machine-learning-engineer-fulfillment-planning.json","meta":{"generated_at":"2026-10-19T18:22:32Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":14267,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-20T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":3685},"rest":"https://alion.io/mcp/rest/get_company?id=3685"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fdoordash-staff-machine-learning-engineer-fulfillment-planning"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fdoordash-staff-machine-learning-engineer-fulfillment-planning"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fdoordash-staff-machine-learning-engineer-fulfillment-planning"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/doordash-staff-machine-learning-engineer-fulfillment-planning\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fdoordash-staff-machine-learning-engineer-fulfillment-planning"}]}