Software Engineer, ML Infrastructure (MDX)

Blue Line Search Group; San Francisco, Sunnyvale (CA, CA); Sur place; USD 131 000 - 192 000; Plein temps

Avantages offerts par ce poste

401(k) with employer matching

Paid parental leave

Wellness benefits

Commuter benefits

Paid time off

Résumé du poste

DoorDash’s MDX team builds the agentic layer of ML infrastructure across DoorDash, Wolt, and Deliveroo. You’ll design and build systems to accelerate ML engineers’ work—from training, evaluation, and deployment to debugging—owning components end to end and collaborating across orchestration, tooling, and observability.

You’ll work with a strong backend foundation, applying AI agents to engineering workflows, and you can grow into technical leadership in a fast-moving area where models, tooling,

Qualifications

• B.S., M.S., or PhD in Computer Science or equivalent.
• 2+ years of industry experience in software engineering.
• Hands-on experience building ML infrastructure in production including feature engineering and feature stores, data pipelines for ML, training and experimentation platforms, model evaluation, deployment, serving and inference, or monitoring.
• Strong backend engineering fundamentals, especially in Python and distributed systems.
• Experience operating systems in production, including testing, observability, debugging, and reliability.
• A good understanding of how ML engineers and data scientists work, and a track record of building platforms, tools, or services that make them more productive.
• Ability to take ambiguous, well-scoped problems from idea to production, and to learn quickly in a fast-moving technical area.
• Proficiency in using AI coding tools (e.g., Claude Code, Codex, Cursor) across the software development lifecycle, including designing, generating code, testing, monitoring, and releasing software.

Responsabilités

• Own well-scoped components end to end, from design through production.
• Work across agent orchestration, tooling and integrations with our ML platform.
• Evaluate agent behavior and observability.
• Apply AI agents to real engineering workflows and grow into technical leadership.

Connaissances

Python

Distributed systems

Backend engineering

Observability

Testing

Debugging

AI coding tools

Formation

B.S., M.S., or PhD in Computer Science

Outils

Kubeflow

MLflow

Ray

Airflow

Kubernetes

AWS

GCP

Claude Code

Codex

Cursor

Description du poste

About the Team

DoorDash's MDX team sits within Machine Learning Platform and builds the shared foundation that ML engineers across DoorDash, Wolt, and Deliveroo rely on to build and run ML-powered products. We work across the full ML lifecycle: feature engineering, training, evaluation, deployment, serving, and monitoring. Our mission is to increase the velocity and reliability of ML-driven business impact across the company. A central pillar of that work is agentic infrastructure. We are building systems that let agents accelerate and operate the ML workflow itself, including auto research, where agents explore and iterate on modeling ideas, and self‑healing systems that detect, diagnose, and remediate failures in ML pipelines and production models with minimal human intervention.

About the Role

You will join a small, high-leverage team building the agentic layer of DoorDash's ML infrastructure. You'll design and build the systems that let agents accelerate how ML engineers across DoorDash, Wolt, and Deliveroo develop, ship, and operate models. That includes auto research systems that explore and iterate on modeling ideas, and agentic developer support that helps ML engineers move through training, evaluation, deployment, and debugging faster. You'll own well‑scoped components end to end, from design through production, working across agent orchestration, tooling and integrations with our ML platform, evaluation of agent behavior, and observability. This role is ideal for an engineer with a strong backend foundation who is excited to apply AI agents to real engineering workflows, learns quickly, and wants to grow into technical leadership in a fast‑moving area where model capabilities, tooling, and best practices change month to month. You' re excited about this opportunity because…

• B.S., M.S., or PhD in Computer Science or equivalent
• 2+ years of industry experience in software engineering
• Hands‑on experience building ML infrastructure in production including feature engineering and feature stores, data pipelines for ML, training and experimentation platforms, model evaluation, deployment, serving and inference, or monitoring
• Strong backend engineering fundamentals, especially in Python and distributed systems
• Experience operating systems in production, including testing, observability, debugging, and reliability
• A good understanding of how ML engineers and data scientists work, and a track record of building platforms, tools, or services that make them more productive
• Ability to take ambiguous, well‑scoped problems from idea to production, and to learn quickly in a fast‑moving technical area
• Proficiency in using AI coding tools (e.g., Claude Code, Codex, Cursor) across the software development lifecycle, including designing, generating code, testing, monitoring, and releasing software

Nice To Haves

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

Compensation

The successful candidate’s starting pay will fall within the pay range listed below and is determined based on job‑related factors including, but not limited to, skills, experience, qualifications, work location, and market conditions. Base salary is localized according to an employee’s work location. Ranges are market‑dependent and may be modified in the future. In addition to base salary, the compensation for this role includes opportunities for equity grants.

DoorDash cares about you and your overall well‑being. That’s why we offer a comprehensive benefits package to all regular employees, which includes a 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 (e.g. Colorado Healthy Families and Workplaces Act). DoorDash also offers medical, dental, and vision benefits, 11 paid holidays, disability and basic life insurance, family‑forming assistance, and a mental health program, among others. To learn more about our benefits, visit our careers page here.

See below for paid time off details:

For salaried roles: flexible paid time off/vacation, plus 80 hours of paid sick time per year. For hourly roles: vacation accrued at about 1 hour for every 25.97 hours worked (e.g. about 6.7 hours/month if working 40 hours/week; about 3.4 hours/month if working 20 hours/week), and paid sick time accrued at 1 hour for every 30 hours worked (e.g. about 5.8 hours/month if working 40 hours/week; about 2.9 hours/month if working 20 hours/week).

The national base pay range for this position within the United States, including Illinois and Colorado.$130,600—$192,000 USD

About DoorDash

At DoorDash, our mission to empower local economies shapes how our team members move quickly, learn, and reiterate in order to make impactful decisions that display empathy for our range of users—from Dashers to merchant partners to consumers. We are a technology and logistics company that started by enabling door‑to‑door delivery, and we are looking for team members who can help us go from a company that is known as the place you order food to a company that people turn to for any and all goods. DoorDash is growing rapidly and changing constantly, which gives our team members the opportunity to share their unique perspectives, solve new challenges, and own their careers. We’re committed to supporting employees’ happiness, healthiness, and overall well‑being by providing comprehensive benefits and perks including premium healthcare, wellness expense reimbursement, paid parental leave and more.

Our Commitment to Diversity and Inclusion

We’re committed to growing and empowering a more inclusive community within our company, industry, and cities. That’s why we hire and cultivate diverse teams of people from all backgrounds, experiences, and perspectives. We believe that true innovation happens when everyone has room at the table and the tools, resources, and opportunity to excel.

Statement of Non-Discrimination: In keeping with our beliefs and goals, no employee or applicant will face discrimination or harassment based on: race, color, ancestry, national origin, religion, age, gender, marital/domestic partner status, sexual orientation, gender identity or expression, disability status, or veteran status. Above and beyond discrimination and harassment based on “protected categories,” we also strive to prevent other subtler forms of inappropriate behavior (i.e., stereotyping) from ever gaining a foothold in our office. Whether blatant or hidden, barriers to success have no place at DoorDash. We value a diverse workforce – people who identify as women, non-binary or gender non‑conforming, LGBTQIA+, American Indian or Native Alaskan, Black or African American, Hispanic or Latinx, Native Hawaiian or Other Pacific Islander, differently‑abled, caretakers and parents, and veterans are strongly encouraged to apply.

Thank you to the Level Playing Field Institute for this statement of non‑discrimination. Pursuant to the San Francisco Fair Chance Ordinance, Los Angeles Fair Chance Initiative for Hiring Ordinance, and any other state or local hiring regulations, we will consider for employment any qualified applicant, including those with arrest and conviction records, in a manner consistent with the applicable regulation.

If you need any accommodations, please inform your recruiting contact upon initial connection.