Base Salary
$137k - $299k/yr
Responsibilities
- Build infrastructure that moves generative AI products, agents, automation, and personalization from prototype to production.
- Develop evaluation SDKs, OpenTelemetry trace and score ingestion, LLM-as-judge workflows, offline and online evaluation pipelines, and agent simulations.
- Design scalable systems for evaluation workflows, LLM observability, agent simulation, data pipelines, and backend services.
- Enable teams to measure model and agent quality, detect regressions, compare models, and manage observability and costs.
- Build production-grade platforms supporting experimentation, latency, scale, monitoring, SLOs, playbooks, and operational excellence.
- Partner with ML engineers, product engineers, data scientists, and platform teams across DoorDash, Wolt, and Deliveroo.
- Help connect evaluation and agent observability signals to automated evaluation, simulation, reward modeling, and RLHF/RLVR evaluation.
Requirements
- A B.S., M.S., or PhD in Computer Science or equivalent.
- At least 3 years of industry software engineering experience.
- Strong backend engineering fundamentals, particularly in Python and distributed systems.
- Experience building production services, APIs, data pipelines, or ML infrastructure at scale.
- Experience operating production systems, including observability, debugging, reliability, incident response, and performance or cost optimization.
- Hands-on experience with evaluation, LLM observability, or measurement systems for production ML/LLM products.
- Proficiency using AI coding tools such as Claude Code, Codex, or Cursor throughout the software development lifecycle.
- Preferred experience with LLM-as-judge methodology, evaluation calibration, eval drift detection, human-in-the-loop labeling, or agent evaluation harnesses.
- Preferred experience with OpenTelemetry, tracing, instrumentation SDKs, AI agents, MCP servers, streaming ingestion, analytical stores, LLM gateways, model routing, developer platforms, Kubernetes, AWS, GCP, high-throughput batch systems, RAG, vector databases, or open-weights LLM inference and fine-tuning.
Benefits
- Comprehensive benefits for regular employees, including 401(k) matching, medical, dental, and vision coverage, disability and basic life insurance, wellness benefits, commuter benefits match, and mental health support.
- 16 weeks of paid parental leave, family-forming assistance, 11 paid holidays, paid time off, and paid sick leave.
- Salaried roles receive flexible paid time off or vacation plus 80 hours of paid sick time per year.
- Equity grant opportunities are included in the compensation package.
- Base salary is localized by work location and varies based on skills, experience, qualifications, location, and market conditions.
Categories
About DoorDash
At DoorDash, our mission to empower local economies shapes how our team members move quickly and always learn and reiterate to support merchants, Dashers and the communities we serve. We are a technology and logistics company that started with door-to-door delivery, and we are looking for team members who can help us go from a company that is known for delivering 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. Our leaders seek the truth and welcome big, hairy, audacious questions. We are grounded in our company values, and we make intentional decisions that are both logical and display empathy for our range of users—from Dashers to Merchants to Customers.