ML Platform Engineer

Aimlroles; San Francisco (CA); Híbrido; USD 131 000 - 192 000; Tempo integral

Resumo da oferta

DoorDash is seeking skilled data scientists and ML engineers to advance our on-demand logistics platform. You will build scalable ML systems for Search, Recommendations, ETA prediction, and Dasher capacity planning in a hybrid setup across San Francisco, Sunnyvale, or Seattle.

You'll collaborate with data scientists and product engineers, deploy models to production, and help design high-performance data pipelines and infrastructure powering trillions of feature values and billions of

Qualificações

• BS/MS/PhD in CS or equivalent.
• Strong CS fundamentals and OOP knowledge.
• 2+ years of industry software engineering experience.
• Prior experience building ML systems in production.
• Experience deploying ML models to production environments.

Responsabilidades

• Build a world-class ML platform for model training, deployment, and inference.
• Collaborate with Data Scientists and Product Engineers to evolve the ML platform.
• Develop high-performance pipelines capable of handling large-scale data.
• Design infrastructure to store trillions of feature values and support billions of predictions daily.
• Drive directions for centralized ML platform powering DoorDash's business.

Conhecimentos

CS fundamentals

OOP languages

Software engineering

ML systems in production

Model deployment

Cloud infrastructure

Formação académica

B.S./M.S./PhD in Computer Science or equivalent

Ferramentas

Pandas

Python ML libraries

PyTorch

TensorFlow

Spark

MLLib

Databricks

MLFlow

Airflow

Dagster

AWS

Descrição da oferta de emprego

DoorDash is seeking skilled data scientists and ML engineers to advance our on-demand logistics platform. You will build scalable ML systems for Search, Recommendations, ETA prediction, and Dasher capacity planning in a hybrid setup across San Francisco, Sunnyvale, or Seattle.

You'll collaborate with data scientists and product engineers, deploy models to production, and help design high-performance data pipelines and infrastructure powering trillions of feature values and billions of