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. 

You can find out more on our ML blog post here

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

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.

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