Quality And Reliability Engineer in San Francisco

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

Figma is growing our team of passionate creatives and builders on a mission to make design accessible to all. Figma’s platform helps teams bring ideas to life—whether you're brainstorming, creating a prototype, translating designs into code, or iterating with AI. From idea to product, Figma empowers teams to streamline workflows, move faster, and work together in real time from anywhere in the world. If you're excited to shape the future of design and collaboration, join us! As Director, People Partners for Product, Design & Engineering (PDE), you'll be partnering with the leaders that are responsible for the teams building Figma and leading a team of highly skilled People Partners. You'll operate as a trusted advisor - coaching, challenging, and guiding the organization through rapid growth, reorganization, and change. As a member of the People team, you’ll partner closely with all of our People functions to build a best in class people function. If you’re energized by ambiguity, adept at building deep relationships, and excited to shape what great People Partnering looks like at Figma, we’d love to hear from you! This is a full time role held from our San Francisco hub. What you'll do at Figma: Serve as the strategic People Partner to Figma’s CTO and Chief Design Officer, building the credibility and trust to influence how they lead, organize, and grow their teams Lead and develop a talented team of People Partners across the Product, Design and Engineering organizations Lead and execute our People Programs such as org design, resource management, performance, and change management through periods of rapid scaling, reorganization, and shifting priorities Drive the core people cycles for your orgs across performance, calibration, talent reviews, succession planning while raising the bar on quality and consistency Partner across the People function and our cross functional partners to help execute the People strategy across the PDE organization Use data and insi

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. The Airports team is part of a mission-critical endeavor that keeps travelers moving smoothly. As an engineer on our team, your role will be essential in making sure drivers and riders enjoy a dependable experience at airports. You'll work hand in hand with various teams across Lyft, fostering collaboration and driving innovation to tackle the unique challenges of the travel and airports industry. Your responsibilities will also involve managing real-time communication with airports, ensuring our technology integrates seamlessly into their operations. Your skills will be the driving force behind enhancing the airport journey for millions. Responsibilities: Drive high-impact projects and innovate new solutions to provide the best user experience. Lead large features from idea to positive execution and launch Write well-crafted, well-tested, readable, maintainable code Participate in code reviews to ensure code quality and distribute knowledge Participate in our teams on call rotation. Identify, triage, debug and resolve issues/bugs across our various applications and platforms Have the ability to explain the various trade offs made in decisions Manage project priorities, deadlines, and deliverables. Experience: BS/MS or equivalent in Computer Engineering, Computer Science, or related field or equivalent practical experience 2-5+ years of software engineering/production infrastructure industry experience Experience with Python, Go Proficiency in object-oriented programming Experience working with data structures or algorithms Ability to work with a low-ego, highly collaborative, and cross-functional team Bonus points: experience pursuing side projects or open-source project Benefits: Great medical, dental, and vision insurance options with additional programs available when enrolled M

About the Team Merchant Analytics helps DoorDash make better product, business, and go-to-market decisions through high-quality analytics, predictive modeling, experimentation, and strategic thought partnership. We work across some of DoorDash’s most important merchant and marketplace priorities, building the measurement, insights, and decision frameworks that improve outcomes for merchants and drive company impact. About the Role We’re hiring two Data Science Managers, each to lead a pod within Merchant Analytics and help shape high-priority product and business decisions. In this role, you will lead a team of data scientists, partner closely with Strategy & Operations, Product, Engineering, and business leaders, and turn ambiguous questions into clear recommendations that influence roadmap and plan outcomes. Success in this role means building a high-performing team, raising the quality and speed of decision-making, and ensuring analytics work is tightly connected to measurable business impact. You will report into Director, Data Science on our Merchant Analytics team in our Analytics organization. You’re excited about this opportunity because you will… Lead and develop a team of data scientists responsible for high-impact analytics, predictive modeling, and decision support tied to DoorDash’s most important product, business, and GTM priorities. Partner closely with Strategy & Operations, Product, Engineering, and business leaders to shape decisions, influence roadmaps, and improve plan-critical metrics. Define success metrics, build measurement frameworks and predictive models, and use experimentation and analysis to connect product and operational levers to business outcomes. Build a high-performing pod that balances analytical rigor, strong prioritization, and clear storytelling in a fast-moving environment. Scale reusable analytics frameworks, tools, models, and best practices that make the broader organization more effective over time. We’re excited

About the Team The Customer Experience team serves as a foundational operations pillar at DoorDash, dedicated to resolving friction within the last mile. We architect and oversee an expansive global network of support centers — spanning both teammate-assisted and AI-driven support — obsessing over the user journey to ensure every interaction is seamless and reliable. As the analytics team, our mission is to make every support interaction measurably better: we define what a great resolution looks like, quantify where we fall short, and turn that into a roadmap for product, operations, and AI/ML partners. We are looking for a Manager to lead and grow the analytics team behind our core support experience. About the Role As a Manager on the Customer Experience Analytics team, you'll set the analytical vision for how DoorDash measures and improves customer resolutions across our global network of support teammates and their interactions with our customers. You'll lead and grow a team of data scientists working at the intersection of customer experience quality and operational cost — uncovering opportunities to drive perfect interactions and informing improvements to teammate tooling that leverages AI-driven resolutions. You'll establish a clear measurement framework for resolution quality, own insights to drive strategy and roadmap, and align partners across CX, Product, Engineering, Operations, and AI/ML. This is a high-visibility leadership role: success means better outcomes for customers, a more effective support organization, and a team of data scientists who are growing in their craft. You're excited about this opportunity because you will… Lead, grow, and develop a team of data scientists — providing mentorship, feedback, and clear career development pathways. Set the analytical vision for the core support experience, defining what a great customer resolution looks like and building the metrics to measure it. Uncover opportunities to drive perfect interactions, tr

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

Who We Are HP IQ is HP’s new AI innovation lab. Combining startup agility with HP’s global scale, we’re building intelligent technologies that redefine how the world works, creates, and collaborates. We’re assembling a diverse, world-class team—engineers, designers, researchers, and product minds—focused on creating an intelligent ecosystem across HP’s portfolio. Together, we’re developing intuitive, adaptive solutions that spark creativity, boost productivity, and make collaboration seamless. We create breakthrough solutions that make complex tasks feel effortless, teamwork more natural, and ideas more impactful—always with a human-centric mindset. By embedding AI advancements into every HP product and service, we’re expanding what’s possible for individuals, organisations, and the future of work. Join us as we reinvent work, so people everywhere can do their best work. About the Role HP IQ is shaping the future of next‑generation experience for HP Customers, and we’re looking for a Program Manager who can help drive that mission. This role sits at the heart of how our teams build, validate, and deliver AI‑powered experiences with exceptional quality and developer efficiency. You’ll lead programs that strengthen QA processes, enhance developer workflows, and accelerate engineering velocity across HP’s AI product portfolio. Success in this role requires a blend of technical fluency, structured program leadership, and the ability to communicate clearly across—and up—the organization. Responsibilities Program Leadership & Execution Drive end‑to‑end planning, execution, and delivery of QA and Developer Experience programs within the HP IQ organization. Build and maintain program roadmaps, milestones, and KPIs that align with organizational priorities. Identify risks, dependencies, and cross‑team impacts early, and lead mitigation strategies. Ensure consistent alignment across engineering, QA, product, data science, and partner teams. Quality & Developer

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

Location - Hybrid This is a hybrid role based out of our San Francisco, Corporate Headquarter office, 3 days in the office, 2 days remote OR one of our Hub locations, Boston, MA or Raleigh, NC, which means you may be expected to work from a designated co-working space from time to time, and will otherwise work remotely from home, until such time as a dedicated office is established. About Us Sauce Labs is the world’s largest full-lifecycle, test automation platform, and the company behind Selenium. Trusted by 80% of the world’s top ten largest financial institutions and over 300,000 enterprise users, Sauce Labs provides the only AI platform capable of turning business intent into autonomous testing and quality assurance. With a proprietary dataset of 8.7 billion test runs, Sauce Labs empowers the Fortune 2000 to bridge the gap between AI-driven code generation and enterprise-grade software quality. Learn more at http://saucelabs.com . Release Assurance at the Speed of AI | Meet the new Sauce Labs The Role The Senior Director, Growth is an AI-first revenue leader responsible for setting the macro strategy, revenue architecture, and cross-functional alignment of an intelligent, end-to-end pipeline engine. Reporting to executive leadership, this role bridges marketing and sales executive strategy—focusing on expanding our outbound/inbound SDR function, driving predictive pipeline models, and enabling functional marketing leads to scale their teams. Rather than managing day-to-day tactical execution, you will focus on high-level channel architecture, budget optimization, sales leadership alignment, and scaling our revenue operations to maximize global pipeline output. Responsibilities Pipeline Strategy & Executive Revenue Alignment Align on global pipeline target setting, forecasting models, and macro growth strategy across inbound and outbound channels. Champion an agentic AI revenue stack, equipping functional leaders and teams with predictive tools, d

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 the Team DoorDash’s GenAI Platform team sits within Machine Learning Platform and builds the shared infrastructure that helps DoorDash, Wolt, and Deliveroo teams safely bring GenAI-powered products, agents, automation, and personalization to production. Our mission is to increase the velocity of business impact from GenAI. A central pillar of that work is our evaluation platform — the unified evals backbone that lets teams measure, trace, and trust the quality of LLM and agent systems across the company, powering trace/score ingestion, LLM-as-judge workflows, agent simulations, and LLM observability for the tens of millions of daily requests flowing through our LLM Gateway. We also own core platform surfaces including the Agent Gateway, open-weights model serving and batch inference, guardrails, and cost attribution. About the Role You will join a small, high-leverage team building production infrastructure for Generative AI at DoorDash, with a primary focus on our evals and LLM observability platform: the systems that let teams evaluate, trace, and continuously improve the quality of LLM and agent products. You’ll work across evaluation frameworks and SDKs, OpenTelemetry-based trace/score ingestion, LLM-as-judge and offline/online eval pipelines, agent simulations, data pipelines, backend services, and observability. This role is ideal for an engineer who enjoys building reliable measurement and quality primitives in a fast-moving technical area where product needs, model capabilities, vendor ecosystems, and evaluation methodologies are evolving quickly. You’re excited about this opportunity because you will… Build the infrastructure that helps DoorDash teams move GenAI ideas from prototype to production, increasing the velocity of business impact from AI across the company. Work on our unified evals platform — evaluation SDKs, OpenTelemetry trace/score ingestion, LLM-as-judge, offline and online eval pipelines, and agent simulations — alongside the LLM Gatew

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. The vision of the Safety & Customer Care (SCC) team is to foster long-term loyalty to Lyft with every support interaction. If we are successful, a Lyft customer will rarely interact with Lyft Support. But when that interaction occurs, their issue is resolved quickly, effectively, and with true care. For a Lyft customer, their experience of Support should be that “Lyft cares about me and made the experience easy.” As an Analytics Lead, you’ll partner directly with cross-functional stakeholders to identify opportunities and design solutions for improving our customers’ support experience. You’ll leverage your analytical expertise to deliver actionable insights and recommendations to drive quality business decisions with customer-facing impact. The ideal candidate is a critical thinker and exceptional problem solver who can build strong relationships with different teams, and who is eager to serve as a leader within the broader Support organization to drive our business forward. Responsibilities Own the analytical integrity of safety data at Lyft. Set the definitions, inclusion criteria, and reconciliation logic behind every stated figure. Serve as the primary data liaison to external data auditors, ensuring clarity, consistency, and quality of safety data used in external reporting. Maintain documentation standards that ensure continuity across reporting cycles and compliance with reporting requirements. Run the publication cycle end to end: definitions freeze, data lock, QA, leadership review, sign-off. Catch definitional drift before it reaches a published number. Serve as the analytics counterpart to Business, Legal, Policy, and Communications on Safety data. Move safety reporting from volume counts to diagnosis: which categories are growing, where reported incidence diverges from ac

About Scale Scale’s mission is to develop reliable AI systems for the world’s most important decisions. As the leading AI data foundry, we provide the high-quality data and full-stack technologies that power the world’s most advanced models — fueling breakthroughs in generative AI, defense, and autonomous vehicles. We partner with leading enterprises and governments to bring AI into production that performs when it matters most, combining rigorous evaluation with full-stack deployment so our customers can build AI they can trust. About the Team Applied Intelligence Systems (AIS) is part of the Scale Generative AI Platform (SGP), focused on pushing the frontier of what agentic applications can do across diverse enterprise and government use cases. We build the infrastructure and tooling that power agentic AI in production, paired with applied ML research, design, and evaluation to ensure these systems perform reliably at the scale our customers demand. AIS spans multiple workstreams — agent evaluation and oversight, orchestration and tool-use infrastructure, model and systems optimization, and applied research on new agent capabilities — and this role is not scoped to any single one of them. We’re growing fast, with increasing traction across both commercial and public sector customers, and we’re just getting started — this team will define what dependable, production-grade agentic AI looks like. About the Role As a Staff Machine Learning Research Engineer, you will operate across the full breadth of AIS’s technical needs — wherever the hardest ML problem in agentic AI happens to be that quarter. This could mean training and fine-tuning models, designing evaluation and observability systems, building improvement loops from production data, prototyping novel agent architectures, or designing internal systems and tooling that boost productivity across teams. You’re not tied to one team’s roadmap; you’re expected to move to where the technical leverage is highest, and t

About Scale AI 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. Reinforcement learning environments are now the center of gravity for that work: the difference between a model that demos well and a model that reliably completes long-horizon work is almost always the quality of the environments and reward signals it was trained against. Responsibilities As a Staff Software Engineer, RL Environments, you'll own the technical foundation for how Scale builds, runs, verifies, and delivers RL environments at scale. An RL environment is a real piece of software: a containerized world with real dependencies, real state, real tools, and a grader that has to be correct even when the agent is creative about breaking it. Building one is a full-stack engineering problem. Building thousands of them reproducibly, cheaply, with trustworthy reward signals and throughput measured in millions of rollouts is a systems problem that very few people have solved. You'll work on both. You'll design the platform: sandboxed execution, environment packaging and versioning, rollout orchestration, trajectory capture, verifier frameworks, and the authoring surfaces that let engineers and domain experts produce environments without reinventing infrastructure each time. And you'll go deep on the environments themselves by instrumenting real applications, designing task suites that expose specific capability gaps, and building graders that