About the Team
For a complete understanding of this opportunity, and what will be required to be a successful applicant, read on.
Come help us build the world's most reliable on-demand logistics engine for last-mile grocery and retail delivery! We're looking for an experienced Senior Software Engineer, Machine Learning 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 expert to join our team. As a Senior Machine Learning Engineer, you’ll be conceptualizing, designing, implementing, and validating algorithmic improvements to the catalog system and our product knowledge graph 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, and category classification, image classification.
- Partner with engineering, product, and business strategy leaders to help shape an 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
- 5+ 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 fields.
- 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), Graph-based Models, and Computer Vision.
- The desire for impact with a growth-minded and collaborative mindset.
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