Senior Machine Learning Engineer, New Verticals Agentic Foundations

DoorDash is hiring a Senior Machine Learning Engineer to support Agentic Foundations and focus on Vertical Agent Development. In this hybrid role in Seattle, you will drive continuous improvements to flagship agents using an eval-driven loop and help extend the approach to new merchant and dasher agentic experiences.

Role Summary

You will be responsible for iterating on core agent capabilities, starting with the Ask grocery assistant. The work is grounded in evaluation and experimentation, with a goal of improving agent speed, cost-efficiency, and reliability for large-scale customer usage. You will also help transfer proven methods into production-ready agents for merchants and dashers.

Key Responsibilities

• Own continuous improvement of flagship agents (beginning with the Ask Assistant) using an eval-driven loop to improve speed, cost-efficiency, and reliability for millions of customers.
• Extend the eval-driven approach to new agentic experiences for Merchants and Dashers, transforming promising ideas into production-ready agents.
• Build and refine an eval harness-optimization loop to identify failure modes, then iterate on prompts, tools, skills, and context while measuring impact on real customer tasks.
• Run rigorous experiments, including fine-tuning open-weights models and deploying small language models (SLMs) to replace or augment larger LLMs when appropriate.
• Identify and drive agentic opportunities for Merchants and Dashers from early exploration through production rollout.
• Collaborate on agentic memory, agent-compatible product representations, and post-training SLMs for steerable generative recommendation, bringing these capabilities into production agents.
• Partner with engineering, product, and business leaders to define an ML-driven strategy for DoorDash’s fast-growing grocery and retail delivery business.

Required Qualifications

• 3+ years of industry machine learning experience, including hands-on development and shipping of LLM-based agents (tool use, context management, prompting, guardrails) and improving them using evals and data.
• Experience with post-training or fine-tuning of open-weights models (SFT, preference optimization, or RL), ideally involving small language models, with sound judgment on quality, latency, and cost trade-offs.
• Strong foundation in NLP and machine learning, with proficiency in Python and frameworks such as PyTorch or TensorFlow.
• M.S. or PhD in Computer Science, Statistics, Math, or another quantitative field, or equivalent practical experience, along with a collaborative, growth-minded approach and a focus on measurable impact.

Technologies

• Python
• PyTorch
• TensorFlow
• SFT
• Preference optimization
• RL

Team and Approach

Agentic Foundations is part of New Verticals ML and builds core AI/ML intelligence that powers high-quality, scalable agents at DoorDash. The team validates progress through flagship agent experiences such as the Ask grocery assistant.

Work is executed through a closed-loop process: new models, evals, and representations improve agents, while real-world agent usage highlights gaps that inform subsequent foundations work.

Location and Reporting

• Location: Seattle, WA (hybrid)
• Reporting line: engineering lead on the New Verticals AI/ML team
• Work model: hybrid with some time in-office and some time remote

Compensation and Eligibility

• Salary range: USD 167,800 - 246,800 per year
• Minimum experience: 3 years

Benefits

• Premium healthcare
• Wellness expense reimbursement
• Paid parental leave

Notice to Applicants (NYC or Remote Jobs Associated with NYC Office)

We used Covey as part of our hiring and/or promotional process for jobs in NYC and certain features may qualify it as an AEDT in NYC. We provided Covey with job requirements and candidate submitted applications. We began using Covey Scout for Inbound from August 21, 2023, through December 21, 2023. We resumed using Covey Scout for Inbound again on June 29, 2024, and ceased using Covey Scout for Inbound on April 30, 2026. The Covey tool has been reviewed by an independent auditor. Results of the audit may be viewed here: https://getcovey.com/nyc-local-law-144.

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