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Software Engineer, Machine Learning Platform - Gen AI

DoorDash USASan Francisco, CA; Sunnyvale, CA; Seattle, WA313 Infrastructure Engineering
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Salary
$130,600 — $192K USD
Job type
Full-time
Experience
Senior · 3+ yrs
Posted
8 Oct 2026
Status
Open · checked 7d ago

About this role

This role suits an engineer who enjoys pushing the cost and performance frontier of GPU inference and fine-tuning in a fast-moving technical environment. The Software Engineer, Machine Learning Platform - Gen AI position is based in San Francisco, CA, Sunnyvale, CA, or Seattle, WA, within DoorDash.

Role Overview

DoorDash is hiring a Software Engineer for the GenAI Platform team within the Machine Learning Platform organization. The team builds shared infrastructure that helps DoorDash, Wolt, and Deliveroo safely bring generative AI products, agents, automation, and personalization to production. The position focuses on open-weights model platforms spanning real-time GPU serving, high-throughput batch inference, and model fine-tuning.

Key Responsibilities

Build infrastructure that transitions generative AI ideas from prototype to production to increase business impact across DoorDash.
Work on the open-weights serving stack including real-time GPU endpoints, high-throughput batch inference, and fine-tuning methods like SFT, DPO, and LoRA, alongside LLM Gateways, Agent Gateways, evaluations, guardrails, and cost attribution.
Design scalable and high-performance systems for model serving, batch inference, GPU autoscaling, and fine-tuning to power customer and internal automation use cases.
Optimize GPU inference cost and latency by reducing batch processing times and decreasing inference costs while providing reliable model selection choices.
Construct platforms supporting rapid experimentation that meet production standards for latency, scale, monitoring, SLOs, and operational playbooks.
Collaborate closely with machine learning engineers, product engineers, data scientists, and platform teams across DoorDash, Wolt, and Deliveroo.
Shape future centralized GenAI platform directions such as reinforcement learning, agent optimization, and post-training techniques.

Requirements

B.S., M.S., or PhD in Computer Science or an equivalent field.
Minimum of 3 years of industry experience in software engineering.
Strong backend engineering fundamentals with proficiency in Python and distributed systems.
Experience building production services, APIs, data pipelines, or machine learning infrastructure at scale.
Experience operating production systems including observability, debugging, reliability, incident response, and performance or cost optimization.
Hands-on experience with LLM inference or fine-tuning of open-weight models in production environments.
Ability to navigate ambiguous and fast-moving technical areas to build reusable platform capabilities.
Proficiency in using AI coding tools throughout the software development lifecycle.

Nice to Have

Experience with LLM inference engines and serving frameworks such as vLLM, SGLang, and TensorRT-LLM in production.
Experience with distributed and multi-node fine-tuning and training pipelines including SFT, DPO, RLHF, and LoRA.
GPU performance work involving multi-node inference, memory optimization, quantization, or cold-start and throughput tuning.
Experience with Kubernetes, cloud infrastructure like AWS or GCP, GPUs, serverless GPU platforms, or high-throughput batch systems.
Experience with LLM gateways, model routing, vendor abstraction, or cost attribution.
Experience building developer platforms, internal platforms, or self-serve infrastructure.
Experience building and deploying AI agents or MCP servers in production.
Experience with evaluation systems, LLM observability, tracing, RAG, search, or vector databases.

Skills and Tools

Python
Distributed Systems
LLM Inference and Fine-Tuning (SFT, DPO, LoRA)
GPU Serving and Autoscaling
vLLM, SGLang, TensorRT-LLM
Kubernetes, AWS, GCP, Modal
AI Coding Tools (Claude Code, Codex, Cursor)

Salary and Benefits

The national base pay range for this position in the United States is $130,600 to $192,000 USD, with localization according to work location and additional opportunities for equity grants. Comprehensive benefits include a 401(k) plan with employer matching, 16 weeks of paid parental leave, wellness benefits, commuter benefits match, medical, dental, and vision coverage, 11 paid holidays, disability and basic life insurance, family-forming assistance, a mental health program, flexible paid time off, and 80 hours of paid sick time per year.

About the Company

DoorDash is a technology and logistics company that started by enabling door-to-door delivery and has expanded into a platform supporting local economies and diverse user needs. The organization operates across multiple regions including the United States, supporting brands like DoorDash, Wolt, and Deliveroo.

How to Apply

To apply for this role, please visit the official DoorDash careers page.

Skills and tech stack

PythonvLLMSGLangTensorRT-LLMKubernetesAWSGCPModalClaude CodeCodexCursorLLMLLMsRAGReinforcement LearningMachine LearningFine-tuningGenerative AIDistributed Systems

Questions candidates ask

What is the salary range for this role?

The base pay range is $130,600 to $192,000 USD, determined by factors such as skills, experience, qualifications, and work location, plus equity grants and benefits.

What locations are available for this position?

This position is located in San Francisco, CA, Sunnyvale, CA, or Seattle, WA.

What experience level is required?

The role requires a minimum of 3 years of industry experience in software engineering and a degree in Computer Science or equivalent.

What specific technical stack is used for GenAI tasks?

The work involves Python, distributed systems, open-weight models, LLM inference engines like vLLM and SGLang, Kubernetes, cloud platforms, and AI coding tools.

What benefits are provided by DoorDash?

Benefits include a 401(k) with employer matching, medical, dental, and vision coverage, 16 weeks of paid parental leave, flexible paid time off, paid sick leave, wellness benefits, and life insurance.

Ready to apply?

The application is on the official DoorDash USA careers page.

Apply on company site