Product Development Engineer in San Francisco

About the Role At Sigma, we’re not just adding AI—we’re building the future of how people work with data. Our platform already lets users explore billions of rows of data in seconds with a spreadsheet-like interface, analyze and present their data in workbooks, and build data apps and workflows. Now we’re pushing further, applying AI to reshape how people build in Sigma, discover insights, and make smarter decisions—fast. That’s where you come in. As an AI/ML Engineer, you’ll join a growing team focused on building the AI foundation that will power Sigma for the future. Your work will become an integral part of the workflow for the thousands of enterprises that run on Sigma. What You’ll Do Partner with product, design, and engineering teams to identify high-impact AI/ML opportunities Prototype and productionize AI systems that feel intuitive but do a lot under the hood—recommendations, natural language interfaces, agentic workflows, and more Develop and scale AI/ML infrastructure that powers both internal tooling and customer-facing features Tackle novel UX problems at the intersection of AI, BI, and apps What You Bring Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field (required) 10+ years of experience building and deploying production-grade AI/ML systems Deep knowledge of machine learning, deep learning, and applied AI Experience across the full ML lifecycle: data curation, training, deployment, monitoring A track record of building things that ship—whether it’s recommendations, search, machine translation, or something equally complex Experience adapting or training foundation models (language or multimodal) for novel domains Bonus Points (or skills you’ll build here) You've built agents that can plan, reason, and use tools You know your way around cloud infrastructure (AWS, GCP, Azure) You’ve worked in a fast-moving startup or high-growth environment Additional Job details The base salary range for this posit

Sr. Content Marketing Manager Location: San Francisco, CA · In-office 4 days/week Team: Strategic Marketing Reports to: Sr. Director, Strategic Marketing About the role Sigma produces a lot of content — blog, video, product launches, thought leadership — and this role is the editorial backbone that makes all of it sharper, faster, and on brand. You'll run the Sigma blog end-to-end, raise the quality bar on everything that ships, and build the systems and internal bench that let us scale content without losing voice or accuracy. This is a senior, hands-on editorial role for someone who edits with both technical judgment and taste. You'll work shoulder-to-shoulder with PMs and engineers to keep content accurate, coach employees and contractors to produce great work, and bring new thinking to how Sigma earns awareness. You'll join an established content team and won't have to do it all yourself — a Content Producer partners with you on publication and operations. This role reports to the Sr. Director of Strategic Marketing, with room to grow into people management as Sigma's content team scales. What you'll own Editorial standards and editing Edit a high volume of blog posts, balancing technical nuance with taste. You're comfortable editing in the data, analytics, apps, or AI space — you don't need to know everything, but you know what you don't know, flag it, and lean on PMs and engineers to keep content accurate and clear. Keep Sigma's content on brand across every channel and format. Reinforce the standards that contribute to great content: Clear positioning, high-quality imagery, and connected messages across multiple content pieces. Blog and AEO operations Run the Sigma blog end to end: calendar, editorial standards, and publication. Manage the AEO content calendar and the relationship with Sigma's AEO contractor, ensuring 5 AEO blogs are edited, SME-reviewed, and published each week. The team's Content Producer supports publication, with you s

About the Role At Sigma, we’re not just adding AI—we’re building the future of how people work with data. Our platform already lets users explore billions of rows of data in seconds with a spreadsheet-like interface, analyze and present their data in workbooks, and build data apps and workflows. Now we’re pushing further, applying AI to reshape how people build in Sigma, discover insights, and make smarter decisions—fast. That’s where you come in. As an AI/ML Engineer, you’ll join a growing team focused on building the AI foundation that will power Sigma for the future. Your work will become an integral part of the workflow for the thousands of enterprises that run on Sigma. What You’ll Do Partner with product, design, and engineering teams to identify high-impact AI/ML opportunities Prototype and productionize AI systems that feel intuitive but do a lot under the hood—recommendations, natural language interfaces, agentic workflows, and more Develop and scale AI/ML infrastructure that powers both internal tooling and customer-facing features Tackle novel UX problems at the intersection of AI, BI, and apps What You Bring Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field (required) 10+ years of experience building and deploying production-grade AI/ML systems Deep knowledge of machine learning, deep learning, and applied AI Experience across the full ML lifecycle: data curation, training, deployment, monitoring A track record of building things that ship—whether it’s recommendations, search, machine translation, or something equally complex Experience adapting or training foundation models (language or multimodal) for novel domains Bonus Points (or skills you’ll build here) You've built agents that can plan, reason, and use tools You know your way around cloud infrastructure (AWS, GCP, Azure) You’ve worked in a fast-moving startup or high-growth environment Additional Job details The base salary range for this posit

About the role: Are you a relationship builder? Are you curious to learn about customers and passionate about giving them the best customer experience? Are you a self starter and thrive in a dynamic and fast-paced environment where you can make a difference in creating playbooks and processes? We’re looking for a Renewals Manager to be the post-sales quarterback for our corporate customers. In this role, you will be responsible for renewing and generating expansion opportunities. You will work with your Sigma colleagues to maximize customer value and to grow their business. Responsibilities: Develop professional and personal relationships with key stakeholders within each customer account Partner with Customer Success to minimize attrition, identify growth opportunities, drive adoption and increase usage Work with customers to create a strategy for achieving goals and assist Customer Success with removing barriers to business growth Collaborate closely with internal stakeholders such as Product, Engineering, and Alliances. Be able to communicate feedback and insights to the business. to improve product and customer experience Serve as an advocate for our customers and set appropriate expectations Leverage data to effectively guide meaningful customer conversations Facilitate business reviews to accomplish goals and opportunities Help identify opportunities for improvement in existing processes Required Skills / Experience: 2+ years working in Renewals / Customer Success role Ability to react and adapt to potential rapid shifts in priorities and organizational policies Strong negotiation and objection handling skills that allow for value-based contract negotiations Strong process management and detail oriented skills Strong customer management skills, including soft skills Additional Job details The base salary range for this position is $100k - 120k annually. Compensation may vary outside of this range depending on a number of factors, incl

Airtable is the no-code app platform that empowers people closest to the work to accelerate their most critical business processes. More than 500,000 organizations, including 80% of the Fortune 100, rely on Airtable to transform how work gets done. Airtable’s infrastructure is evolving to meet the needs of our fast growing engineering org. We are looking for infrastructure engineers to join our team to help improve critical product infrastructure, with a focus on building systems that have a great developer experience and will scale as we grow. We currently have openings on: Asynchronous Serving: The Asynchronous Serving team is scaling critical systems used by Airtable’s most essential and up-and-coming product features, especially AI features. Upcoming projects include refactoring our background task queue to track its tasks in DynamoDB, adding quality of service to the job queue, and revamping a streaming service to handle 10x scale while being more resilient. Compute: The compute pod builds and manages our Kubernetes-based platform that supports every service at Airtable, including all new AI services such as vector databases, AI evals store, and document extraction and understanding services. We have a lot of exciting foundational work in our roadmap, such as Overhauling our network stack and service discovery, to simplify service setup and strengthen security Region level disaster recovery, and bringing up compute platform from 0->1 in a new region Building custom Kubernetes operators for reliably managing some of our most critical workloads Developer Platform : The Developer Platform team sits at the intersection of all engineering at Airtable, focusing on building the internal tooling, frameworks, and CI/CD systems that power our product teams. We strive to streamline developer workflows - from build and test cycles to production deployments—and foster a best-in-class developer experience. Join us if you’re passionate about creating high-lever

Scale GP (Scale Generative AI Platform) is an enterprise-grade Generative AI platform that provides APIs for knowledge retrieval, inference, evaluation, and more. We are looking for a strong engineer to join our team and help us build and scale our product in a fast-paced environment. The ideal candidate will have a strong understanding of software engineering principles and practices, as well as experience with large-scale distributed systems. You will be responsible for owning large new areas within our product, working across backend, frontend, and interacting with LLMs and ML models. You will solve hard engineering problems in scalability and reliability. You will: Own large new areas within our product Work across backend, frontend, and interacting with LLMs and ML models Deliver experiments at a high velocity and level of quality to engage our customers Work across the entire product lifecycle from conceptualization through production Be able, and willing, to multi-task and learn new technologies quickly Ideally you'd have: 7+ years of full-time engineering experience, post-graduation Experience scaling products at hyper growth startups Experience tinkering with or productizing LLMs, vector databases, and the other latest AI technologies Proficient in Python or Javascript/Typescript, and SQL Experience with Kubernetes Experience with major cloud providers (AWS, Azure, GCP) 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 during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval

Director of Engineering, Physical AI Role Overview The Director of Engineering will report to the General Manager of Physical AI, and will be responsible for leading a multi-disciplinary engineering organization. In this senior leadership role, you will own the execution of the Physical AI Data Engine — the platform powering the next generation of Physical AI/Embodied AI. You will collaborate closely with Operations and GTM to guide product direction and help solve the data bottleneck that stands between today's robotics research and real-world deployment. This role requires significant ownership in a fast-paced environment and you will motivate internal teams to set the pace for business growth. Travel will come into play. Key Responsibilities: Set and drive the technical vision across data collection infrastructure, teleoperation systems, ML training pipelines, model evaluation frameworks, annotation tooling, and research Lead a multidisciplinary engineering organization—spanning engineering managers, software engineers, ML engineers, and ML research scientists—while designing the organizational structure, talent strategy, and culture required to scale rapidly without compromising on quality or strategic alignment Maintain exceptional technical and operational excellence by deeply understanding team deliverables, asking incisive questions, identifying slipping standards early, and knowing precisely when to step in Drive cross-functional alignment across Engineering, Operations, and GTM on platform architecture, release processes, and shared priorities Collaborate with researchers and clients to architect and deliver scalable, production-grade data infrastructure tailored for complex robotics workloads Required Qualifications: Bachelor's degree in Engineering, Robotics, Computer Science, or a related technical field 8+ years of engineering experience in fast-paced environments, including 4+ years direct people management demonstrated history of recruiting, mentorin

Scale GP is Scale's enterprise Generative AI platform—APIs and infrastructure for knowledge retrieval, inference, evaluation, and intelligent automation. We power mission-critical workflows for leading enterprises, helping teams turn complex data and models into reliable, production-ready AI systems. We're building a new AI Enablement team to create the next generation of agent-powered tools that ground AI in real operational workflows. Our goal: help internal teams demystify their own workflows, then deploy agentic systems that reason over data, take action, and deliver measurable outcomes. We don't build in a vacuum. You'll use our own platform to solve real business problems internally—then selectively commercialize that same stack for customers. What we run on is what we sell. This is a 0→1 team. We're looking for a sharp, product-minded engineer who thrives in ambiguity, moves fast, and loves building systems from scratch alongside customers and cross-functional partners. You'll work closely with product, forward-deployed engineers, data scientists, and applied AI teams to turn real-world problems into scalable production solutions. If you like shipping fast, owning outcomes, and working across the stack—from polished frontends to distributed backends to LLM integrations—this role is for you. What You’ll Do Own full-stack features and projects end-to-end — from design through production deployment — within a larger product area Sample surfaces - Accounting Agents, Finance Copilots, GTM Agents, Agentic Experimentation Platforms Develop reliable backend services in Typescript/Python, work with distributed systems, data pipelines, and AI/ML infrastructure Integrate LLMs, vector databases, and agentic frameworks to power intelligent workflows Ship quickly through tight experimentation loops while maintaining high quality and reliability Adapt across the stack and learn new tools as needed to solve real problems end-to-end Ideal Experience 3+ years of full-tim

About the Team Our US Marketplace team is responsible for growing the DoorDash business in the US, helping customers to discover & order what’s best in their city, merchants to grow their sales, and dashers to find flexible work. About the Role The US Marketplace team is looking for a motivated and hands-on Associate Manager to join the Strategy & Operations Growth and Markets team. You will own a portfolio of projects aimed at growing the core Marketplace business, working closely with DoorDash’s product, marketing, finance, and analytics teams.You’ll have the opportunity to help grow strategic markets, identify new growth bets, incubate 0-1 experiments, and execute on a roadmap to drive growth. You’re excited about this opportunity because you will… Build and own. You’ll have your fingerprints all over DoorDash’s next wave of growth. You’ll do whatever it takes to launch, get 1% better every day, and scale something completely new, from high-level strategy down to the nitty-gritty operational details. Incubate. You’ll take bets that don’t have an owner yet, scope them, test them, and either graduate them into funded programs or kill them with a clear, well-argued recommendation. Strategize. From first principles, you’ll develop the optimal strategy for growing segments and launching bets that no existing playbook covers. Experiment. You’ll turn strategies into operational experiments that create measurable, actionable outcomes, then use those results to shape the larger implementation plan. Analyze. You’ll pull your own data, assess the operational and financial impact of your decisions, and iterate based on what you find. Lead and collaborate. You’ll work with cross-functional partners across product, analytics, marketing, sales, and finance to get your initiatives resourced and shipped. We’re excited about you because… You have 4+ years of experience in a problem-solving role: consulting, tech, banking, or similar. Experience taking something

About the Team The Storage organization builds and operates the online stateful systems and abstractions that DoorDash Engineering depends on: reliable, efficient, secure, and easy to use. Within Storage, the Distributed Caching team owns every caching offering at DoorDash end to end, including ElastiCache (Redis/Valkey), Boulder (our KVRocks-based key-value store for high-QPS feature serving), Entity Cache (read Bill Shen’s engineering blog post, “ High-Performance Proxy Cache for DoorDash Services ”), and the Distributed Lock Service, plus the smart clients (asgard-redis, valkey-go) that sit in front of them. These systems back critical product surfaces across DoorDash, Wolt, and Deliveroo: the team runs roughly 400 ElastiCache clusters serving hundreds of millions of GET requests per second in aggregate, and Boulder, our offline-to-online feature store, serves billions of feature lookups per second at peak. About the Role The team owns provisioning of clusters and the smart clients that sit in front of them, baking in sensible defaults so that other engineering teams get a turnkey caching solution instead of having to run their own. You'll help drive Boulder's evolution to scale further, improve cost efficiency, enhance performance, and support real-time updates; re-platform the Distributed Lock Service onto a strongly consistent backend; and build the self-serve tooling and recommendation engine that let customers describe a workload (QPS, TTL, payload size, latency profile) and get the right backend without talking to a human. You'll go deep on cache invalidation, replication, sharding, compaction, and failover, while shipping the guardrails, automation, and observability that keep this scale operable by a small team. You must be located in San Francisco, Seattle, or the New York Metro Area for this hybrid position. You will report to the Engineering Manager on the Distributed Caching team within the Storage organization. You’re excited about this opportunity b

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 The DoorDash Research Fellowship is a 3-month program (extendable to 6 months) looking for Summer and Fall 2026 cohorts, for researchers and engineers who want to work on the hardest applied ML and AI problems in local commerce. Fellows are given the resources, autonomy, and access to real-world operational data needed to pursue ambitious research directions — with the goal of producing work that influences both the field and how DoorDash operates at scale. This program is modeled on the best external research fellowships: fellows are treated as independent researchers, not as junior employees on a product team. You pick the problem (within a set of priority areas), you own the direction, and you publish or ship the outcome. You’re excited about this opportunity because you will receive… Dedicated compute allocation sized to the research agenda — GPU clusters for training and inference budgets for experimentation Full access to DoorDash's research infrastructure — our internal RL stack, training and evaluation pipelines, RL environments built on real operational systems, agent evaluation harnesses, and the tooling our own research teams use day-to-day. Fellows are first-class users, not sandboxed visitors. Access to DoorDash operational data — real-world datasets spanning logistics, merchant operations, consumer behavior, and marketplace dynamics, under appropriate data governance Research mentorship from senior researchers and engineering leaders at DoorDash, plus a named research sponsor for each fellow who meets with you weekly and is accountable for unblocking your work Speaker series featuring leading researchers and practitioners from academia and industry — faculty from top ML programs, research leads from frontier AI labs, and senior operators from across tech. Fellows get dedicated 1:1 time with speakers when possible. A cohort of fellows working alongside you — a small, tight-knit group of researchers tackling different problems but sharing

About the Team DoorDash Digital Ordering is DoorDash’s leading SaaS business unit, offering a suite of products across online ordering, branded websites and mobile apps, loyalty solutions, and more that enable restaurants to reach customers and grow their revenue through their own first-party channels. The business is one of the fastest-growing segments within DoorDash, and yet is only scratching the surface of a generational opportunity to better serve hundreds of thousands of merchants across the Americas to help them grow their business and improve working lives in one of the country’s biggest industry sectors. Strategy & Operations sits at the center of that opportunity. The team partners with Product to set the strategy and vision for every offering in the suite, across our SMB and enterprise merchants. We decide what to build, where to invest, and how to bring it to market, and we learn by putting products in front of merchants and running the experiments that show us what moves their business. As part of this team, the Associate Manager will take end-to-end ownership of a set of products and lead the cross-functional effort to grow them. Your work will be instrumental to helping transition DoorDash from a consumer marketplace to an industry-leading B2B SaaS company. About the Role As an Associate Manager on the Digital Ordering Strategy & Operations team, you will own a set of products within our first-party suite from end to end. You will set the strategy and priorities for those products in partnership with Product, be accountable for their growth, and lead the Product, Engineering, Analytics, Implementation, Sales, and Marketing partners who bring them to market. This role is ideal for a strategic operator who can move fast and wear many hats, equal parts analyst, builder, operator, and cross-functional leader. You will own zero-to-one experiments alongside products already operating at scale, help shape the roadmap with Product, and work directly

About the Team The Merchant (Mx) AI/ML team is a cornerstone of DoorDash’s merchant organization. We empower our restaurant partners to thrive on DoorDash by building intelligent, scalable AI systems that simplify operations, elevate their digital presence, and enhance customer engagement. Our world-class machine learning engineers develop production-grade AI solutions that power the entire merchant lifecycle — from onboarding and store setup to menu management, growth, and real-time order operations. The team is deeply customer-obsessed and impact-driven, focused on turning cutting-edge research in LLMs, multimodal learning, generative AI, and agentic automation into products that make our merchants more successful every day. About the Role We’re looking for an Engineering Manager to lead the Mx AI/ML team, driving the design and deployment of next-generation AI product solutions that power our merchant experiences. This is a highly cross-functional leadership role — you’ll collaborate with product, design, operations, and data science teams to define the AI roadmap, guide technical direction, and deliver end-to-end AI/ML solutions at massive scale. You’ll lead a team of talented ML engineers who are building real AI products delivered to merchants’ fingertips, helping them become more successful on DoorDash. You’re excited about this opportunity because you will… Lead and grow a team of exceptional AI/ML engineers developing production-grade machine learning and generative AI solutions for the merchant ecosystem. Define a multi-year strategy and execute the AI roadmap across key Mx pillars — Onboarding, Menu Media Understanding & Generation, Menu Metadata Intelligence, and Agentic Task Automation. Partner with product and operations to translate merchant pain points into scalable AI-powered solutions. Own the end-to-end lifecycle of ML systems — from ideation and experimentation to productionization and continuous improvement. Drive innovation in multimodal AI

About the Team DoorDash is looking for an Engineering Manager to lead our Discovery Experience team, which owns the Homepage - DoorDash’s front door. It’s the first screen millions of consumers see every day, and since every session starts there, it’s the highest-leverage surface in the consumer funnel: a more personalized recommendation, a faster render, or a cleaner layout can move the metrics the whole company watches. The Homepage spans restaurants, grocery, and emerging verticals across iOS, Android, and Web. We’re rebuilding it around LLM-generated recommendations, shifting discovery from static, rules-based feeds to generative, intent-driven experiences that respond to real-time signals in the moment. About the Role You will lead and grow a team of product-focused full stack engineers, owning both the product and technical direction for the discovery surface - deciding where discovery goes next and how it’s built. You’ll set the roadmap and drive execution alongside Product, Design, Data Science, and ML/Recommendation Platform partners, and you’ll own the quality, velocity, and consumer impact your team ships. It’s a role with real ownership and the room to grow both the product and the team behind it. You’re excited about this opportunity because you will… Own the Homepage end to end, the highest-traffic surface at DoorDash and where every consumer session begins Turn Homepage bets into company-level outcomes: real lift in conversion and order rate for millions of consumers Define discovery quality for DoorDash: getting the right store, restaurant, or item in front of the right consumer at the right moment Ship LLM-gen recommendations and intent-aware discovery that route consumers to the right experience across food, grocery, retail, and emerging verticals Partner across Product, Design, Data Science, and ML/Recommendation Platform teams to shape the discovery roadmap and ship the experiences behind it Build an inclusive, high-performing team by coaching en