Staff Software Engineer, Machine Learning - Personalization

Staff Software Engineer, Machine Learning - Personalization San Francisco, CA; Sunnyvale, CA 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. 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 applying ML Mentor junior team members, and lead cross functional pods to create collective impact We’re excited about you because you have… 8+ years of industry experience developing machine learning models with business impact, and shipping ML solutions to production 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 About DoorDash DoorDash is a technology and logistics company focused on empowering local economies. We’re growing rapidly and offer a comprehensive benefits package to regular employees, including health benefits, paid parental leave, and other wellness and financial benefits. Our Commitment to Diversity and Inclusion We’re committed to growing and empowering a more inclusive community within our company, industry, and cities. 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. We value a diverse workforce and strongly encourage applicants from all backgrounds to apply. If you need accommodations, please inform your recruiting contact upon initial connection. Benefits and Compensation The compensation for this role includes base salary and opportunities for equity grants. Base salary is localized according to work location and market conditions. See below for example base pay ranges by level (subject to change):

I4 — $137,100 - $201,600 USD

I5 — $167,800 - $246,800 USD

I6 — $203,500 - $299,300 USD

Apply for this job If you are interested in this position, please proceed with the application process through our careers portal. #J-18808-Ljbffr DoorDash USA