Senior Software Engineer, ML Training Platform

Who you are

You have 5+ years of experience in software engineering, particularly in building scalable systems that support machine learning initiatives. Your background includes a strong understanding of data transformations and distributed model training, and you are comfortable collaborating with cross-functional teams including ML engineers and data scientists. You are proficient in Python and have experience with Kubernetes, which allows you to design resilient pipelines for model training. You value clean, high-performance code and are committed to maintaining high standards of quality and reliability in your work.

You are excited about the opportunity to drive key training initiatives and own significant sub-projects that enhance the performance and usability of the ML Training Platform. Your experience with machine learning frameworks such as PyTorch and LightGBM will enable you to contribute effectively to the team. You thrive in a collaborative environment and are eager to work closely with various stakeholders to refine requirements and set realistic milestones.

Desirable

Experience with GPU-accelerated training and familiarity with real-time decision-making systems will be advantageous. You are also open to learning new technologies and methodologies that can improve the platform's capabilities.

What you'll do

In this role, you will take ownership of major projects within the ML Training Platform, focusing on creating reliable and extensible solutions for data transformations and distributed model training. You will architect and implement scalable solutions that optimize for both short-term speed and long-term maintainability. Your responsibilities will include collaborating with ML engineers, platform engineers, and product stakeholders to ensure that the platform supports high-volume training in a fast-evolving environment.

You will drive key training initiatives by owning and delivering significant sub-projects that enhance the platform's performance and reliability. This includes designing resilient pipelines for distributed model training and ensuring that the solutions you implement are both effective and efficient. You will set a high bar for quality and reliability, leading by example with clean, high-performance code and thorough design reviews.

What we offer

DoorDash offers a hybrid work environment, allowing you to work from our offices in San Francisco, Sunnyvale, or Seattle while also providing flexibility for remote work. You will be part of a dynamic team that is committed to building the world’s most reliable on-demand logistics engine, impacting millions of orders each day. We encourage you to apply even if your experience doesn't match every requirement, as we value diverse perspectives and backgrounds in our team.

We provide competitive compensation and benefits, along with opportunities for professional growth and development within the company. Join us in shaping the future of logistics and machine learning at DoorDash.