Software Engineer, ML Infrastructure (MDX)

DoorDash•San Francisco, WA

13h

About The Position

The Software Engineer will join DoorDash’s MDX team within Machine Learning Platform, building shared infrastructure that ML engineers across DoorDash, Wolt, and Deliveroo use throughout the ML lifecycle. The team’s mission is to increase the velocity and reliability of ML-driven business impact, including by developing agentic systems that can accelerate and operate ML workflows. The role focuses on building the agentic layer of DoorDash’s ML infrastructure. The engineer will design and build systems for auto research, where agents explore and iterate on modeling ideas, and agentic developer support that helps engineers work through training, evaluation, deployment, and debugging. The role owns well-scoped components from design through production, spanning agent orchestration, integrations with the ML platform, evaluation of agent behavior, and observability. The position suits an engineer with strong backend fundamentals who is interested in applying AI agents to real engineering workflows and growing toward technical leadership in a fast-moving area. The work emphasizes production standards such as reliability, safety guardrails, cost controls, monitoring, and clear playbooks, with close partnership across ML engineering, data science, and platform teams.

Requirements

B.S., M.S., PhD in Computer Science, or equivalent.
At least 2 years of industry experience in software engineering.
Hands-on experience building production ML infrastructure, such as feature engineering and feature stores, ML data pipelines, training and experimentation platforms, model evaluation, deployment, serving and inference, or monitoring.
Strong backend engineering fundamentals, especially in Python and distributed systems.
Experience operating production systems, including testing, observability, debugging, and reliability.
Understanding of how ML engineers and data scientists work, and a track record of building platforms, tools, or services that improve their productivity.
Ability to take ambiguous but well-scoped problems from idea to production and learn quickly in a fast-moving technical area.
Proficiency using AI coding tools such as Claude Code, Codex, or Cursor throughout the software development lifecycle, including designing, generating code, testing, monitoring, and releasing software.

Nice To Haves

Experience building production LLM-powered applications or AI agents, including tool use, orchestration, or MCP servers, or experience on substantial projects in these areas.
Experience with agent evaluation, LLM observability, tracing, or building evaluation harnesses.
Experience with ML platforms or MLOps tooling such as Kubeflow, MLflow, Ray, or Airflow.
Experience with Kubernetes and cloud infrastructure such as AWS or GCP.
Experience building developer tools, internal platforms, or self-serve infrastructure.
Experience with guardrails, safety, or cost controls for LLM systems.

Responsibilities

Build agentic systems that help ML engineers move from idea to production model faster across DoorDash, Wolt, and Deliveroo.
Design and implement infrastructure that allows agents to propose, run, and evaluate modeling experiments.
Build agentic developer support for ML workflows, including assistance with training jobs, pipeline debugging, deployment reviews, and platform navigation.
Develop evaluation and observability for agent behavior to measure effectiveness, identify regressions, and support greater autonomy.
Apply production standards to agentic workflows, including reliability, safety guardrails, cost controls, monitoring, and playbooks.
Partner with ML engineers, data scientists, and platform teams to identify workflow needs and turn them into durable, reusable platform capabilities.
Own well-scoped components end to end, from design through production.

Benefits

401(k) plan with employer matching.
16 weeks of paid parental leave.
Wellness benefits.
Commuter benefits match.
Paid time off and paid sick leave in compliance with applicable laws.
Medical, dental, and vision benefits.
11 paid holidays.
Disability and basic life insurance.
Family-forming assistance.
Mental health program.
Equity grant opportunities.
For salaried roles: flexible paid time off/vacation and 80 hours of paid sick time per year.