DoorDash USA
Machine Learning Engineer - New Verticals
DoorDash USA, San Francisco, California, United States, 94199
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 an experienced machine learning engineer to help us develop the cutting-edge machine learning models that power DoorDash's growing grocery and retail business.
About the Role We’re looking for a passionate Machine Learning Engineer to join our team. You’ll be conceptualizing, designing, implementing, and validating algorithmic improvements to the ranking, fulfillment and catalog system 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 consumer shopping journey delightful, fulfillment system efficient and knowledge graph accurate. We’re looking for someone with a command of production-level machine learning and experience with solving end-user problems who enjoys collaborating with multidisciplinary teams.
You will report to the engineering manager on our New Verticals 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 various shopping and dashing problems including recommendation, search, logistic optimization, product knowledge graph building.
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…
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 Recommendation System, Search, Causal Inference, Optimization, Time Series, Natural Language Processing, Large Language Model, Computer Vision.
Machine learning background in Python; experience with PyTorch, TensorFlow, or similar frameworks.
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
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About the Role We’re looking for a passionate Machine Learning Engineer to join our team. You’ll be conceptualizing, designing, implementing, and validating algorithmic improvements to the ranking, fulfillment and catalog system 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 consumer shopping journey delightful, fulfillment system efficient and knowledge graph accurate. We’re looking for someone with a command of production-level machine learning and experience with solving end-user problems who enjoys collaborating with multidisciplinary teams.
You will report to the engineering manager on our New Verticals 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 various shopping and dashing problems including recommendation, search, logistic optimization, product knowledge graph building.
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…
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 Recommendation System, Search, Causal Inference, Optimization, Time Series, Natural Language Processing, Large Language Model, Computer Vision.
Machine learning background in Python; experience with PyTorch, TensorFlow, or similar frameworks.
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
#J-18808-Ljbffr