DoorDash US

1 month ago

Software Engineer, Machine Learning Infrastructure - Generative AI

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 2 hours agoStatus: Live

Job Summary

Join a small, high-leverage team building production infrastructure for Generative AI. You’ll work across backend services, ML infrastructure, agent/tool orchestration, evaluation systems, model serving, batch inference, and observability to enable GenAI capabilities at scale for DoorDash, Wolt, and Deliveroo.

Location: San Francisco

Workplace: Onsite

Employment Type: Full time

Job Function: Software Engineering

Key Responsibilities

•Build infrastructure that moves GenAI ideas from prototype to production, increasing the velocity of business impact from AI across the company.
•Develop production GenAI platform surfaces including the LLM Gateway, Agent Gateway, evals infrastructure, open-weights model serving, batch inference, fine-tuning, guardrails, and cost attribution.
•Design scalable systems for AI agents, MCP/tool orchestration, retrieval, batch inference, model serving, and evaluation workflows that power customer and internal automation use cases.
•Help product teams choose the right model and vendor strategy across closed-source and open-weight models, with reliability, fallback, observability, and cost controls built in.
•Build platforms that support rapid experimentation while meeting production standards for latency, scale, monitoring, SLOs, playbooks, and operational excellence.

Pay and Benefits

Salary: USD 137,100 - 201,600 annually

Perks:Health Insurance401kPaid LeaveWellness Stipend

Key Requirements

•BS, MS, or PhD in Computer Science or equivalent.
•4+ years of industry experience in software engineering.
•Strong backend engineering fundamentals, especially in Python and distributed systems.
•Experience building production services, APIs, data pipelines, or ML infrastructure at scale.
•Experience operating systems in production, including observability, debugging, reliability, incident response, and performance/cost optimization.

Experience:4+ yearsMachine learningGenAIAI infrastructure

Education:Bachelor's

Skills:CommunicationTeamworkProblem-solvingCollaborationAnalytical thinking

Languages:English

Tech Stack:PythonDistributed systemsKubernetesAWSGCPGPUModel serving

Company Brief

DoorDash US

On-demand logistics platform connecting consumers with local restaurants, grocers, and retailers for food delivery, pickup, and convenience services. Operates a marketplace and last-mile delivery network while offering tools and analytics for merchants and couriers.

Industry: Online Marketplaces

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: San Francisco, United States

Founded: 2013

Website LinkedIn

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DoorDash US

1 month ago

Software Engineer, Machine Learning Infrastructure - Generative AI

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 2 hours agoStatus: Live

Job Summary

Location: San Francisco

Workplace: Onsite

Employment Type: Full time

Job Function: Software Engineering

Key Responsibilities

•Build infrastructure that moves GenAI ideas from prototype to production, increasing the velocity of business impact from AI across the company.
•Develop production GenAI platform surfaces including the LLM Gateway, Agent Gateway, evals infrastructure, open-weights model serving, batch inference, fine-tuning, guardrails, and cost attribution.
•Design scalable systems for AI agents, MCP/tool orchestration, retrieval, batch inference, model serving, and evaluation workflows that power customer and internal automation use cases.
•Help product teams choose the right model and vendor strategy across closed-source and open-weight models, with reliability, fallback, observability, and cost controls built in.
•Build platforms that support rapid experimentation while meeting production standards for latency, scale, monitoring, SLOs, playbooks, and operational excellence.

Pay and Benefits

Salary: USD 137,100 - 201,600 annually

Perks:Health Insurance401kPaid LeaveWellness Stipend

Key Requirements

•BS, MS, or PhD in Computer Science or equivalent.
•4+ years of industry experience in software engineering.
•Strong backend engineering fundamentals, especially in Python and distributed systems.
•Experience building production services, APIs, data pipelines, or ML infrastructure at scale.
•Experience operating systems in production, including observability, debugging, reliability, incident response, and performance/cost optimization.

Experience:4+ yearsMachine learningGenAIAI infrastructure

Education:Bachelor's

Skills:CommunicationTeamworkProblem-solvingCollaborationAnalytical thinking

Languages:English

Tech Stack:PythonDistributed systemsKubernetesAWSGCPGPUModel serving

Company Brief

DoorDash US

Industry: Online Marketplaces

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: San Francisco, United States

Founded: 2013

Website LinkedIn