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Doordash - San Francisco, CA
posted 3 months ago
About the position
The Software Engineer, Machine Learning - Developer Experience role at DoorDash involves building and maintaining a robust machine learning platform that supports various business functions. The position focuses on enhancing machine learning workflows, improving infrastructure reliability, and collaborating with data scientists and product engineers to evolve the platform. This hybrid role is based in San Francisco, Sunnyvale, or Seattle and requires a strong background in software engineering and machine learning systems.
Responsibilities
- Build a world-class ML platform where models are developed, trained, and deployed seamlessly.
- Work closely with Data Scientists and Product Engineers to evolve the ML platform according to their use cases.
- Help build high-performance and flexible pipelines that can rapidly adapt to new technologies and modeling approaches.
- Design infrastructure solutions to store trillions of feature values and support hundreds of billions of predictions daily.
- Drive the direction for the centralized machine learning platform that powers all of DoorDash's business operations.
- Improve the reliability, scalability, and observability of training and inference infrastructure.
Requirements
- B.S., M.S., or PhD. in Computer Science or equivalent.
- Exceptionally strong knowledge of CS fundamental concepts and OOP languages.
- 4+ years of industry experience in software engineering.
- Prior experience building machine learning systems in production, enabling data analytics at scale.
- Experience in developing and deploying machine learning models, even if they are simple proof of concepts.
- Experience in Systems Engineering, particularly in a cloud computing environment.
Nice-to-haves
- Experience with challenges in real-time computing.
- Experience with large scale distributed systems, data processing pipelines, and machine learning training and serving infrastructure.
- Familiarity with Pandas and Python machine learning libraries and deep learning frameworks such as PyTorch and TensorFlow.
- Familiarity with Spark, MLLib, Databricks, MLFlow, Apache Airflow, Dagster, and similar technologies.
- Familiarity with large language models like GPT, LLAMA, BERT, or Transformer-based architectures.
- Experience in a cloud-based environment such as AWS.
Benefits
- 401(k) plan with employer match
- Paid time off
- Paid parental leave
- Wellness benefits
- Paid holidays
- Medical, dental, and vision benefits
- Disability and basic life insurance
- Family-forming assistance
- Commuter benefit match
- Mental health program
