ML Platform Engineer — Production-Scale & Reliability

DoorDash, Inc.; Sunnyvale (CA); Híbrido; USD 131 000 - 192 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

401(k) with employer matching

Paid parental leave

Wellness benefits

Commuter benefits match

Paid time off

Paid sick leave

Medical, dental, and vision benefits

11 paid holidays

Disability insurance

Life insurance

Family-forming assistance

Mental health program

Resumo da oferta

DoorDash, Inc. is hiring data scientists and ML engineers to build and operate a world‑class ML platform for a high‑volume delivery network. You will partner with data scientists and product engineers to deploy scalable models that power search, recommendations, and dasher allocation.

The role emphasizes building robust pipelines, handling trillions of features, and delivering reliable training and inference infrastructure in a hybrid work setup across San Francisco, Sunnyvale, or Seattle.

Qualificações

• Bachelor's, Master's, or PhD in computer science or equivalent
• Strong CS fundamentals and OOP knowledge
• 2+ years of industry software engineering experience
• Prior production ML systems experience
• Experience developing and deploying ML models
• Experience in cloud-based systems and data processing

Responsabilidades

• Build and maintain the ML platform and pipelines
• Collaborate with data scientists and product engineers
• Scale training and inference infrastructure
• Store trillions of feature values and support billions of predictions daily
• Contribute to centralized ML platform strategy and directions
• Improve reliability, scalability, and observability of ML infra

Conhecimentos

CS fundamentals

OOP languages

Software engineering

ML systems

ML models

Cloud infrastructure

Formação académica

B.S./M.S./PhD in CS

Ferramentas

Pandas

Python ML libraries

PyTorch

TensorFlow

Spark

MLFlow

Airflow

Dagster

Databricks

Descrição da oferta de emprego

DoorDash, Inc. is hiring data scientists and ML engineers to build and operate a world‑class ML platform for a high‑volume delivery network. You will partner with data scientists and product engineers to deploy scalable models that power search, recommendations, and dasher allocation.

The role emphasizes building robust pipelines, handling trillions of features, and delivering reliable training and inference infrastructure in a hybrid work setup across San Francisco, Sunnyvale, or Seattle.