Senior Software Engineer, Machine Learning Infrastructure
Jobright.ai
Seattle,
Washington,
United States
Information Technology
H-1B
Job posted on August 7, 2025
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Job Description:
Verified Job On Employer Career Site
Job Summary: DoorDash is a technology and logistics company focused on empowering local economies. The role involves building and maintaining a robust machine learning infrastructure to enhance various company-wide ML workflows, collaborating with Data Scientists and Product Engineers, and ensuring the reliability and scalability of ML 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 as per their use cases • You will help build high performance and flexible pipelines that can rapidly evolve to handle new technologies, techniques and modeling approaches • You will work on infrastructure designs and solutions to store trillions of feature values and power hundreds of billions of predictions a day • You will help design and drive directions for the centralized machine learning platform that powers all of DoorDash's business. • Improve the reliability, scalability, and observability of our training and inference infrastructure.
Qualifications:
Required: • B.S., M.S., or PhD. in Computer Science or equivalent • Exceptionally strong knowledge of CS fundamental concepts and OOP languages • 6+ years of industry experience in software engineering • Prior experience building machine learning systems in production such as enabling data analytics at scale • Prior experience in machine learning - you've developed and deployed your own models - even if these are simple proof of concepts • Systems Engineering - you've built meaningful pieces of infrastructure in a cloud computing environment. Bonus if those were data processing systems or distributed systems
Preferred: • Experience with challenges in real-time computing • Experience with large scale distributed systems, data processing pipelines and machine learning training and serving infrastructure • Familiar with Pandas and Python machine learning libraries and deep learning frameworks such as PyTorch and TensorFlow • Familiar with Spark, MLLib, Databricks, MLFlow, Apache Airflow, Dagster and similar related technologies • Familiar with large language models like GPT, LLAMA, BERT, or Transformer-based architectures • Familiar with a cloud based environment such as AWS
Company: DoorDash is a food delivery platform that connects customers with local and national businesses. It is a sub-organization of DoorDash. Founded in 2013, the company is headquartered in San Francisco, California, USA, with a team of 10001+ employees. The company is currently Public Company. DoorDash has a track record of offering H1B sponsorships.
APPLY NOW
Job Summary: DoorDash is a technology and logistics company focused on empowering local economies. The role involves building and maintaining a robust machine learning infrastructure to enhance various company-wide ML workflows, collaborating with Data Scientists and Product Engineers, and ensuring the reliability and scalability of ML 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 as per their use cases • You will help build high performance and flexible pipelines that can rapidly evolve to handle new technologies, techniques and modeling approaches • You will work on infrastructure designs and solutions to store trillions of feature values and power hundreds of billions of predictions a day • You will help design and drive directions for the centralized machine learning platform that powers all of DoorDash's business. • Improve the reliability, scalability, and observability of our training and inference infrastructure.
Qualifications:
Required: • B.S., M.S., or PhD. in Computer Science or equivalent • Exceptionally strong knowledge of CS fundamental concepts and OOP languages • 6+ years of industry experience in software engineering • Prior experience building machine learning systems in production such as enabling data analytics at scale • Prior experience in machine learning - you've developed and deployed your own models - even if these are simple proof of concepts • Systems Engineering - you've built meaningful pieces of infrastructure in a cloud computing environment. Bonus if those were data processing systems or distributed systems
Preferred: • Experience with challenges in real-time computing • Experience with large scale distributed systems, data processing pipelines and machine learning training and serving infrastructure • Familiar with Pandas and Python machine learning libraries and deep learning frameworks such as PyTorch and TensorFlow • Familiar with Spark, MLLib, Databricks, MLFlow, Apache Airflow, Dagster and similar related technologies • Familiar with large language models like GPT, LLAMA, BERT, or Transformer-based architectures • Familiar with a cloud based environment such as AWS
Company: DoorDash is a food delivery platform that connects customers with local and national businesses. It is a sub-organization of DoorDash. Founded in 2013, the company is headquartered in San Francisco, California, USA, with a team of 10001+ employees. The company is currently Public Company. DoorDash has a track record of offering H1B sponsorships.