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Machine Learning Systems Engineer at DoorDash USA

1 month ago


San Francisco, California, United States DoorDash USA Full time
About the Role

DoorDash USA is seeking an experienced Machine Learning Systems Engineer to join our team in San Francisco, Sunnyvale, or Seattle. This is a hybrid opportunity that combines software engineering and machine learning expertise to build systems that empower efficient machine learning at scale.

Key Responsibilities
  • Design and develop high-performance and flexible pipelines for machine learning workflows
  • Collaborate with Data Scientists and Product Engineers to evolve the ML platform as per their use cases
  • Work on infrastructure designs and solutions to store trillions of feature values and power hundreds of billions of predictions a day
  • Improve the reliability, scalability, and observability of our training and inference infrastructure
Requirements
  • Bachelor's degree in Computer Science or equivalent
  • Strong knowledge of computer science fundamental concepts and object-oriented programming languages
  • At least 4 years of industry experience in software engineering
  • Prior experience building machine learning systems in production
  • Prior experience in machine learning and system engineering
Nice To Haves
  • Experience with real-time computing challenges
  • Experience with large-scale distributed systems, data processing pipelines, and machine learning training and serving infrastructure
  • Familiarity with Pandas, Python machine learning libraries, PyTorch, TensorFlow, Spark, MLLib, Databricks, MLFlow, Apache Airflow, Dagster, and related technologies
Benefits

We offer competitive salaries ranging from $160,000 - $200,000 per year, depending on experience and qualifications, plus benefits including health insurance, retirement plan, and generous paid time off. Our company culture values diversity, equity, and inclusion, and we strive to create a workplace where everyone feels welcome and empowered to succeed.