Machine Learning Engineer - New Verticals - Search & Recommendations

Machine Learning Engineer - New Verticals - Search & Recommendations DoorDash | Posted Mar 11 Apply Full-time Negotiable Unknown 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 a talented machine learning engineer to help us develop the cutting edge search and information retrieval 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 Machine Learning Scientist, you’ll be conceptualizing, designing, implementing, and validating algorithmic improvements to the search and personalization experiences at the heart of our fast growing grocery and retail delivery business. You will leverage 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 be expected to demonstrate a strong command of production level machine learning, a passion for solving end‑user problems, leadership skills to collaborate well with multi-disciplinary teams, and execution focus to prioritize effectively in a dynamic environment. You’re Excited About This Opportunity Because You Will… 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 leveraging ML. Mentor junior team members, and lead cross functional pods to generate collective impact. You can find out more on our ML blog here We’re Excited About You Because You Have… 5+ years of industry experience developing machine learning models with business impact, and shipping ML solutions to production. Deep expertise in applied ML for Search/NLP/IR/RecSys - both classical and deep learning based. Additional familiarity with explore/exploit/MAB algorithms, LLMs, and causal inference techniques are a plus. Strong machine learning background in Python; experience with PyTorch or TensorFlow preferred. Familiarity with Kotlin/Scala are a plus. Great communication skills - written and verbal. M.S., or PhD. in Statistics, Computer Science, Math, Operations Research, Physics, Economics, or other quantitative field High-energy and confident — 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 You’re an owner — driven, focused, and quick to take ownership of your work Humble — you’re willing to jump in and you’re open to feedback Adaptable, resilient, and able to thrive in ambiguity as things change quickly in our fast‑paced environment! Growth‑minded — you’re eager to expand your skill set and excited to carve out your career path in a hyper‑growth setting Desire for impact — ready to take on a lot of responsibility and work collaboratively with your team 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. 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. 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). Pay Ranges

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. 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. 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 “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. Accommodations If you need any accommodations, please inform your recruiting contact upon initial connection. #J-18808-Ljbffr SupportFinity™