About The Team Come help us build the world's most reliable on-demand, logistics engine for last-mile grocery and retail delivery! We're looking for a skilled machine learning engineer to help us develop the cutting-edge NLP and product knowledge graph models that power DoorDash's growing grocery and retail business. About The Role We’re looking for a passionate Applied Machine Learning engineer to join our team. As a Machine Learning Engineer, you will conceptualize, design, implement, and validate algorithmic improvements to the catalog system and our product knowledge graph, which is 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. You will report into the engineering manager on our New Verticals, Catalog ML 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 solve catalog building and quality problems such as entity recognition, entity resolution, attribute extraction, category classification, and image classification. Partner with engineering, product, and business strategy leaders to help shape our ML-driven product roadmap and grow a multi-billion dollar retail delivery business. Find new ways to use diverse data sources, intuitive models, and flexible experimentation to create a world-class shopping and dashing experience. We're Excited About You Because You Have… 1+ years of industry experience post PhD or 3+ years of industry experience post graduate degree of developing machine learning models with business impact. Experience with machine learning methods in building product knowledge graphs. Machine learning background in Python; experience with PyTorch, TensorFlow, or similar frameworks and familiarity with Natural Language Processing (LLM, Entity Recognition, Entity Resolution, Classification), and Graph-based Models. M.S., or PhD. in Statistics, Computer Science, Math, Operations Research, Physics, Economics, or other quantitative fields. The desire for impact with a growth-minded and collaborative mindset. 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. 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 with door-to-door delivery, and we are looking for team members who can help us go from a company that is known for delivering food to a company that people turn to for any and all goods. 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. Seniority level Mid-Senior level Employment type Full-time Job function Engineering and Information Technology Industries Software Development #J-18808-Ljbffr DoorDash
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