Quality Associate in San Francisco

About the Team As one of DoorDash's core operations teams, Customer Experience ensures that when issues arise across the platform, there is a reliable and effective support system in place. Our team designs, manages, and continuously improves DoorDash's global support network, with the goal of delivering a high-quality and consistent customer experience. This role sits within the Safety Customer Experience team, focused on the most critical and high-risk incidents on the platform. The team owns some of the most sensitive customer interactions at DoorDash, where thoughtful operational and product decisions directly improve customer trust and platform safety. About the Role You'll operate at the intersection of Product, Operations, and Customer Experience to improve how DoorDash prevents, identifies, and responds to the most critical safety incidents on the platform. You'll partner closely with Product, Policy, Analytics, and Operations to design scalable solutions that deliver accurate, timely support during customers' highest-stakes moments. This role requires a detail-oriented operator who can navigate complex problem spaces, design scalable processes, and execute with precision in a fast-paced environment. You’ll be expected to take ownership of ambiguous, high-stakes problems and translate them into structured, actionable solutions. You’re excited about this opportunity because you will… Drive Safety Strategy – Partner with cross-functional teams to identify and execute initiatives that improve how DoorDash prevents, identifies, and responds to safety incidents. Own End-to-End Experience – Design and optimize the full lifecycle of safety incident handling, including reporting, workflows, support execution, and tooling. Drive Data-Driven Decisions – Leverage data and case-level insights to identify root causes, measure performance, and prioritize opportunities to improve the safety customer experience. Influence Cross-Functionally – Collaborate with Product, Engin

About The Team DoorDash for Business is building the premier corporate dining and benefits platform—helping companies of all sizes feed their teams through industry-leading products and meal programs. Our mission is to become the go-to solution for executives, administrators, and employees who need seamless, high-quality food programs at work. We move fast, operate with an ownership mindset, and are growing new product lines to better serve our corporate customers. Merchant success is core to that mission. When merchants have a clear, fast, and high-quality path from interest to live, our products work better for everyone—customers, Dashers, and the merchants themselves. About The Role As Associate Manager, Merchant Onboarding and Experience on the DoorDash for Business team, you will own how merchants get onto our programs and how they feel while they do it. You will be the lead for onboarding process design, execution quality, and merchant experience—turning a complex, multi-step journey into something that is faster, clearer, and consistently excellent. Your responsibilities will range from strategic (mapping the end-to-end onboarding journey, setting the operating model, and aligning Product, Ops, Sales, and Support on what “great” looks like) to operational (diagnosing drop-off, tightening handoffs, building playbooks, and using data and automation to remove friction). You will bring a systems mindset: every broken step is a process to redesign, every merchant complaint is a signal, and every manual workaround is a candidate for a better workflow. You will report into the DoorDash for Business Merchant Experience team. You’re excited about this opportunity because you will be driving… Onboarding Process Ownership Own the end-to-end merchant onboarding journey—from first intake through go-live. Map the current-state workflow, identify bottlenecks and failure points, and redesign the process so merchants get live faster with fewer drop-offs, fewer handoffs, and c

About the Team DoorDash Labs is an independent team within DoorDash. We explore robotics and automation to transform last-mile logistics in the long term. If you want to work on commercializing autonomy and robotics in a service used by millions of people — and on bringing the merchant partners who power that service along with us — then we want to talk to you! About the Role Come help us redefine last-mile logistics through robotics, automation, and other advanced technologies. Autonomy only works when merchants — restaurants, retailers, and other partners — can reliably interact with our robots: handing off orders, troubleshooting edge cases, and trusting the experience enough to keep using it. This role owns that side of the equation. We're looking for a Merchant Success & Growth lead to build the strategy and operational mechanisms that get merchants onboard, keep them performing, and turn their day-to-day reality into a tight feedback loop for product and engineering. You're excited about this opportunity because you will… Own merchant adoption and performance KPIs for autonomy end-to-end — defining what "successful merchant interaction with a robot" means, instrumenting it, and driving improvement against it. Build the playbooks and operational mechanisms to onboard merchants to autonomy — from first conversation through training, go-live, and steady-state ops — and scale them across markets. Partner with sales, account management, and field ops to recruit and ramp the right merchant cohorts for each stage of the product, and design experiments that test new merchant-facing features and handoff models. Define merchant performance benchmarks (handoff success rate, dwell time, dasher/robot interaction quality, merchant CSAT) and run the cadence that holds partners and internal teams accountable to them. Stand up the feedback loop from the field back to product and engineering — turning merchant complaints, edge cases, and frontline observations into prioriti

About the Team DashMart is a local-fulfillment center owned and operated by DoorDash, offering customers household essentials and other items to their doorsteps with speed, reliability, and quality. Customers order their convenience, grocery, retail, and prepared foods in the DoorDash app, and our team members fulfill orders in a real, brick-and-mortar store for Dashers to deliver. We’re open early and close late - some sites even run 24/7! About the Role DashMart is looking for a motivated and experienced individual that excels in fast-paced, physical environments and is excited to roll up their sleeves and actively engage in day-to-day operations. In this role, you will work within a local fulfillment center supporting Site Management running great shifts, and delegating tasks. As a Shift Lead, you will have shift responsibility for fulfilling orders in a warehouse environment and maintaining inventory, and in some locations, this involves preparing food in a light-prep kitchen. You’re excited about this opportunity because you will… Be an Owner: Take ownership of your assigned shifts, including warehouse and kitchen processes, safety/cleanliness, quality, and training. Maintain accountability for inventory, equipment, and other company assets to ensure they are properly handled, stored, and protected from loss or theft. Delight Customers: Ensure customer orders are delivered with high quality by executing orders accurately, communicating with customers when issues arise, and making sure Dasher pickups go smoothly. Lead: Guide Operations Associates through their shift by ensuring the team works safely and productively and serving as the point of escalation for daily operations. One Team One Fight: Support operations in both the warehouse and kitchen, assist with day-to-day tasks, and lead by example. You will be expected to engage in professional and respectful interactions with team members and customers, ensuring a positive and safe

About the Team The Code Quality team sits within the Developer Platform organization and owns the systems that keep DoorDash's codebase healthy and secure as it scales: static analysis, quality gates, test frameworks, regression infrastructure, and tooling. Our job is to make sure the signals engineers rely on before shipping — test results, coverage, performance feedback etc — are fast and trustworthy. The decisions we make about tooling and standards directly shape how confidently and quickly engineering teams at DoorDash can ship to production. About the Role We're looking for Software Engineers to help build and maintain the systems that validate code quality across DoorDash's engineering org, treating our tooling as a critical product for the engineers who rely on it every day: static analysis and quality gates, test frameworks and regression infrastructure. You’ll design the tooling and automation that will help derive trustworthy quality signals, integrate them into the development lifecycle, and make it easy for engineers to execute reliable, repeatable workflows. You will collaborate across the engineering org, partnering directly with the teams who use what you build to understand the accuracy, reliability and performance of their functionality. You will report into the Engineering Manager on our Code Quality team in our Developer Platform organization. You must be located in either San Francisco, CA, Sunnyvale, CA, Los Angeles, CA, Seattle, WA, or New York, NY. You're excited about this opportunity because you will… Build and maintain quality tooling — static analysis, quality gates, coverage reporting, test frameworks, regression infrastructure — and integrate it directly into our developer workflows and CI/CD pipelines Define and derive quality signals - flakiness, pass rate, coverage, performance, scale readiness etc - Build tooling that improves everyday engineering workflows, including local development, CI/CD, debugging, and rollou

About Glean: Glean is the Work AI platform that helps everyone work smarter with AI. What began as the industry’s most advanced enterprise search has evolved into a full-scale Work AI ecosystem, powering intelligent Search, an AI Assistant, and scalable AI agents on one secure, open platform. With over 100 enterprise SaaS connectors, flexible LLM choice, and robust APIs, Glean gives organizations the infrastructure to govern, scale, and customize AI across their entire business - without vendor lock-in or costly implementation cycles. At its core, Glean is redefining how enterprises find, use, and act on knowledge. Its Enterprise Graph and Personal Knowledge Graph map the relationships between people, content, and activity, delivering deeply personalized, context-aware responses for every employee. This foundation powers Glean’s agentic capabilities - AI agents that automate real work across teams by accessing the industry’s broadest range of data: enterprise and world, structured and unstructured, historical and real-time. The result: measurable business impact through faster onboarding, hours of productivity gained each week, and smarter, safer decisions at every level. Recognized by Fast Company as one of the World’s Most Innovative Companies (Top 10, 2025), by CNBC’s Disruptor 50, Bloomberg’s AI Startups to Watch (2026), Forbes AI 50, and Gartner’s Tech Innovators in Agentic AI, Glean continues to accelerate its global impact. With customers across 50+ industries and 1,000+ employees in more than 25 countries, we’re helping the world’s largest organizations make every employee AI-fluent, and turning the superintelligent enterprise from concept into reality. If you’re excited to shape how the world works, you’ll help build systems used daily across Microsoft Teams, Zoom, ServiceNow, Zendesk, GitHub, and many more - deeply embedded where people get things done. You’ll ship agentic capabilities on an open, extensible stack, with the craf

About Glean: Glean is the Work AI platform that helps everyone work smarter with AI. What began as the industry’s most advanced enterprise search has evolved into a full-scale Work AI ecosystem, powering intelligent Search, an AI Assistant, and scalable AI agents on one secure, open platform. With over 100 enterprise SaaS connectors, flexible LLM choice, and robust APIs, Glean gives organizations the infrastructure to govern, scale, and customize AI across their entire business - without vendor lock-in or costly implementation cycles. At its core, Glean is redefining how enterprises find, use, and act on knowledge. Its Enterprise Graph and Personal Knowledge Graph map the relationships between people, content, and activity, delivering deeply personalized, context-aware responses for every employee. This foundation powers Glean’s agentic capabilities - AI agents that automate real work across teams by accessing the industry’s broadest range of data: enterprise and world, structured and unstructured, historical and real-time. The result: measurable business impact through faster onboarding, hours of productivity gained each week, and smarter, safer decisions at every level. Recognized by Fast Company as one of the World’s Most Innovative Companies (Top 10, 2025), by CNBC’s Disruptor 50, Bloomberg’s AI Startups to Watch (2026), Forbes AI 50, and Gartner’s Tech Innovators in Agentic AI, Glean continues to accelerate its global impact. With customers across 50+ industries and 1,000+ employees in more than 25 countries, we’re helping the world’s largest organizations make every employee AI-fluent, and turning the superintelligent enterprise from concept into reality. If you’re excited to shape how the world works, you’ll help build systems used daily across Microsoft Teams, Zoom, ServiceNow, Zendesk, GitHub, and many more - deeply embedded where people get things done. You’ll ship agentic capabilities on an open, extensible stack, with the craf

About Glean: Glean is the Work AI platform that helps everyone work smarter with AI. What began as the industry’s most advanced enterprise search has evolved into a full-scale Work AI ecosystem, powering intelligent Search, an AI Assistant, and scalable AI agents on one secure, open platform. With over 100 enterprise SaaS connectors, flexible LLM choice, and robust APIs, Glean gives organizations the infrastructure to govern, scale, and customize AI across their entire business - without vendor lock-in or costly implementation cycles. At its core, Glean is redefining how enterprises find, use, and act on knowledge. Its Enterprise Graph and Personal Knowledge Graph map the relationships between people, content, and activity, delivering deeply personalized, context-aware responses for every employee. This foundation powers Glean’s agentic capabilities - AI agents that automate real work across teams by accessing the industry’s broadest range of data: enterprise and world, structured and unstructured, historical and real-time. The result: measurable business impact through faster onboarding, hours of productivity gained each week, and smarter, safer decisions at every level. Recognized by Fast Company as one of the World’s Most Innovative Companies (Top 10, 2025), by CNBC’s Disruptor 50, Bloomberg’s AI Startups to Watch (2026), Forbes AI 50, and Gartner’s Tech Innovators in Agentic AI, Glean continues to accelerate its global impact. With customers across 50+ industries and 1,000+ employees in more than 25 countries, we’re helping the world’s largest organizations make every employee AI-fluent, and turning the superintelligent enterprise from concept into reality. If you’re excited to shape how the world works, you’ll help build systems used daily across Microsoft Teams, Zoom, ServiceNow, Zendesk, GitHub, and many more - deeply embedded where people get things done. You’ll ship agentic capabilities on an open, extensible stack, with the craf

You will: Source and acquire quality candidates for high volume positions to meet hiring and activation goals Review applications and screen candidates Support candidates throughout the recruiting process Partner with other growth recruiters, ops leads and cross-functional leaders to understand Scale’s business needs, then devise and execute on the recruiting strategy needed to deliver on them. Follow and manage processes that will evolve over time as the company grows. Represent and champion the brand, promoting its value proposition to candidates and driving engagement. Represent Scale at occasional onsite growth recruiting events. Ideally you have: 2+ years of recruiting/sourcing experience in a fast-paced, high-growth environment. Excellent written and verbal communication skills, with the ability to tailor messaging to diverse audiences Experience sourcing candidates and filling high volume roles Experience acting as the primary candidate liaison, delivering white-glove service through timely updates and personalized support throughout the interview process Nice to have: Previous experience in a start-up. Either experience managing a full-cycle recruiting experience, or a passion and ability to learn to do so. Experience with various tools such as Linkedin Recruiter, Clay, Modernloop, Gem Extreme attention to detail AI builder, AI-forward operator, or strong interest in agentic coding and experimenting with AI tooling The hourly salary range for this position is $40 to $55/hr. This is a remote position with occasional travels required for onsite growth recruiting events. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allow

About the Team The Support Quality team’s vision is to “Provide teammates, team leads, and AI Agents with actionable feedback on 100% of cases so they can get 1% better every day. Deliver actionable business insight to wider S&O to help improve business policy and processes / Product teams to increase our customer experience.” About the Role You will report to the Director, Teammate Enablement, in our Customer Experience organization. The Teammate Enablement Team is responsible for ensuring that our Teammates have the resources (tooling, quality measurements, and knowledge base) and training to effectively and empathetically support DoorDash’s customers. Where opportunities are identified, we drive feedback to our business partners in order to empower Teammates to be 1% better every day for our customers. The team’s primary role will be to: i) build automated QA metrics that have high coverage, precision, and low false-positive rates; ii) support all manual QA efforts, including incubation and scale-up of new measurements; iii) deliver actionable insights to our partner teams to help improve the processes and policies on our support experience, as well as insights for our vendors to drive better agent performance management; and iv) manage our QA tech providers to ensure they deliver against our ambitious roadmap. This is a leadership role, with the expectation of managing the priorities of a small team while remaining accountable to key initiatives oneself. You’re excited about this opportunity because you will… Lead a small team centered around identifying and fixing top opportunities in our quality assurance programs that support customer service at DoorDash. Design, launch, and evolve our conversational intelligence program, utilizing AI technology to monitor, measure, and drive continuous improvements in our customer service interactions. Drive the strategy of our quality assurance program, identifying the right strategies to balance manual quality assuranc

Scale works with the industry’s leading AI labs to provide high quality data and accelerate progress in GenAI research. We are looking for Research Scientists and Research Engineers with expertise in LLM post-training (SFT, RLHF, reward modeling). This role will focus on optimizing data curation and eval to enhance LLM capabilities in both text and multimodal modalities. In this role, you will develop novel methods to improve the alignment and generalization of large-scale generative models. You will collaborate with researchers and engineers to define best practices in data-driven AI development. You will also partner with top foundation model labs to provide both technical and strategic input on the development of the next generation of generative AI models. You will: Research and develop novel post-training techniques, including SFT, RLHF, and reward modeling, to enhance LLM core capabilities in both text and multimodal modalities. Design and experiment new approaches to preference optimization. Analyze model behavior, identify weaknesses, and propose solutions for bias mitigation and model robustness. Publish research findings in top-tier AI conferences. Ideally you’d have: Ph.D. or Master's degree in Computer Science, Machine Learning, AI, or a related field. Deep understanding of deep learning, reinforcement learning, and large-scale model fine-tuning. Experience with post-training techniques such as RLHF, preference modeling, or instruction tuning. Excellent written and verbal communication skills Published research in areas of machine learning at major conferences (NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR, etc.) and/or journals Previous experience in a customer facing role. Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined du

Scale works with the industry's leading AI labs to provide high quality data and accelerate progress in GenAI research. We are looking for Research Scientists and Research Engineers with expertise in LLM post-training (SFT, RLHF, reward modeling) and evaluation. This role is on the evaluation pod within the GenAI Research Organization and will focus on building benchmarks and diagnosing model failure modes in both text and multimodal modalities. In this role, you will develop rigorous evaluations and diagnostic methods that reveal where frontier models fail and why. You will collaborate with researchers and engineers to define best practices in evaluation-driven AI development. You will also partner with top foundation model labs to translate failure analysis into technical and strategic input on the next generation of generative AI models. You will: Analyze model behavior to identify, characterize, and diagnose failure modes in frontier LLMs and Agents. You’ll identify everything from capability gaps and reasoning errors to robustness and alignment issues, all focusing on RCA. Design and build benchmarks and evaluation methods that measure LLM capabilities in both text and multimodal modalities. Apply post-training expertise (SFT, RLHF, reward modeling) to connect observed failures to the data and training interventions that address them. Publish research findings in top-tier AI conferences. Ideally you’d have: Ph.D. or Master's degree in Computer Science, Machine Learning, AI, or a related field. Deep understanding of deep learning, reinforcement learning, and large-scale model fine-tuning. Experience with post-training techniques such as RLHF, preference modeling, or instruction tuning, and with LLM evaluation or benchmark development. Excellent written and verbal communication skills. Published research in areas of machine learning at major conferences (NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR, etc.) and/or journals. Previous experience in a customer facing r

At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. Scale Frontier Data is the organization behind the training and evaluation data that frontier labs depend on. We build the systems, tooling, and expert workflows that turn hard human expertise into signals that models can learn from, across reasoning, coding, agentic tool use, and domain expertise. About our Customer Platform team: Our Customer Platform Team plays a pivotal role in integrating our platform with external systems and ensuring seamless, reliable connectivity for both internal users and customers. As the leader of this team, you’ll drive the strategy, architecture, and development of our connectivity solutions, focusing on API integration, distributed systems, and a robust data platform. Your role will be crucial in maintaining and enhancing our platform’s ability to meet the needs of both our internal and external stakeholders. Responsibilities: Own large areas within our product Comfortable working cross functionally, whether that be internal or external customers Build features end-to-end: front-end, back-end, system design, debugging and testing Deliver experiments at a high velocity and level of quality to engage our customers Work across the entire product lifecycle from conceptualization through production Influence the culture, values, and processes of a growing engineering team Inspire and mentor less experienced engineers Collaborating with cross-functional teams to define, design, and ship new product features and experiences. Requirements: At least 7-10 years of relevant experience is preferred Track record of shipping high-quality products and features at scale Desire to work in a very fast-paced environment Abil

About Snorkel At Snorkel, we believe meaningful AI doesn’t start with the model, it starts with the data. We’re on a mission to help enterprises transform expert knowledge into specialized AI at scale. The AI landscape has gone through incredible changes since 2015, when Snorkel started as a research project in the Stanford AI Lab, to the generative AI breakthroughs of today. But one thing has remained constant: the data you use to build AI is the key to achieving differentiation, high performance, and production-ready systems. We work with some of the world’s largest organizations to empower scientists, engineers, financial experts, product creators, journalists, and more to build custom AI with their data faster than ever before. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler! In September 2026 we raised a $350 million Series E at a $3.5 billion valuation , and we are scaling our engineering and research teams to meet demand. The role Frontier AI data is expensive to make and hard to measure. Every task we deliver is tested against the strongest models, often through many long-running agent rollouts. Your job is to make that process faster, cheaper, and more rigorous with ML and AI You will be one of the early members of ML & Research Engineering at Snorkel. You will study how frontier-grade data is generated and evaluated, form hypotheses, validate them against real production data, and ship the winners at scale. You will shape the discipline's direction, its standards, and the team that grows around it. What you'll work on Efficient agentic evals. Cut the cost of long-horizon agent evaluation with adaptive sampling, statistically grounded early stopping, model cascades, caching, and cheap-first gating. AI model routing. Route every eval and judge call to the cheapest model that clears the quality bar, with fallback, monitoring, and cost attribution. Fine-tuned small models. Fine-tune and serve open-weight models (LoRA and other

At Scale, our mission is to develop reliable AI systems for the world's most important decisions. For 10 years, Scale has provided the high-quality data and full-stack technologies that power the world's leading models, and has helped enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. Public Sector engineers build the core product including the systems required to ingest and process federal datasets that support real-time decision-making in contested environments. As a New Grad Software Engineer on this team, you will own meaningful, mission-facing work from day one: shipping features, sitting with the government stakeholders who use them, and iterating fast. Example Projects Build multi-layered guardrails that keep agents safe and predictable in high-stakes federal environments Optimize data retrieval for agents, including RAG pipelines over large, heterogeneous federal datasets Build orchestration for fleets of asynchronous agents running long-horizon tasks Develop systems that automatically alert users to deviations and anomalies in incoming data Create interfaces that illustrate how an agent reached a decision, so operators can audit and trust its output Develop data pipelines and ML infrastructure that make previously siloed government data sources accessible to agents Build evaluation infrastructure that measures model reliability against mission requirements Ship full-stack tooling that lets analysts query, visualize, and explore mission data Deploy and harden applications into secure, air-gapped, and cloud-native government environments Requirements A graduation date in Fall 2026 or Spring 2027 with a Bachelor's degree (or equivalent) in a relevant field (Computer Science, EECS, Computer Engineering, Statistics) Product engineering expe