Design And Cost Estimation Head in San Francisco

About the Team As DoorDash continues to expand rapidly, our Core Consumer team plays a pivotal role in shaping the consumer experience through enhancing personalization, search relevance, merchandising strategy, app quality, and the overall ordering experience. Our mission is to implement scalable data solutions and provide insights that directly influence our strategic product direction. We are looking for an Analytics Senior Manager to lead our Discovery team. About the Role As a Senior Manager of Data Science/Analytics, you’ll be leading a team of data scientists who are working on improving the consumer experience. You will develop strategic insights and work closely with the product, engineering, strategy and operations teams to actively build and measure the impact of new features. You will oversee our metrics and analytics strategy to inform strategic product direction, offer technical leadership and build processes to support velocity, and partner with data and product engineers to build robust data foundations. You're excited about this opportunity because you will… Lead and develop a team of Data Scientists in investigating complex issues and uncovering key drivers of our business, along with your own contributions as an Individual Contributor Influence the Product and Operations roadmap by making actionable recommendations based on data Interface frequently with senior leadership to showcase your team’s work and tackle complex business problems Drive measurement strategy for the area under scope, defining success metrics and implementing best practices around experiment design and statistical analysis Develop a strategic learning roadmap based on data observations, strategic questions, and hypotheses We're excited about you because you have… A degree in Math, Physics, Statistics, Economics, Computer Science, or a similar domain Experience managing a team of data scientists, and a track record of delivering impactful analyses 8+ years of experience i

About Us Twitch is the world’s biggest live streaming service, with global communities built around gaming, entertainment, music, sports, cooking, and more. It is where thousands of communities come together for whatever, every day. We’re about community, inside and out. You’ll find coworkers who are eager to team up, collaborate, and smash (or elegantly solve) problems together. We’re on a quest to empower live communities, so if this sounds good to you, see what we’re up to on LinkedIn and X , and discover the projects we’re solving on our Blog . Be sure to explore our Interviewing Guide to learn how to ace our interview process. About the Team The Global Partnerships team lies at the heart of Twitch. Our team is dedicated to serving streamers in our Twitch Partner Program from around the world. Our partner managers are custodians of meaningful and enduring relationships with our Partners. Our operations managers lead the execution and efficiency of critical processes used to support the Partner experience. Our program managers design and implement initiatives that acknowledge and enable Partner success. Collectively, we shape and evolve the Partner Program with meticulous care. Every decision is guided by the diverse needs of our streamers, who are the essence of Twitch’s success. About the Role Twitch is looking for a knowledgeable Partnerships Associate to identify, evaluate and develop high-potential creators on Twitch. As the ideal candidate, you are fascinated by creator communities and stay on the cutting edge of creator and influencer trends. You enjoy spotting talent early, understanding what makes creators successful, and helping them build long-term careers on Twitch. In this role, you'll work across two complementary creator pipelines. First, you'll manage Twitch's inbound creator program, identifying creators who are gaining momentum on Twitch and helping them develop into long-term partners. Second, you'll proactiv

About Us Twitch is the world’s biggest live streaming service, with global communities built around gaming, entertainment, music, sports, cooking, and more. It is where thousands of communities come together for whatever, every day. We’re about community, inside and out. You’ll find coworkers who are eager to team up, collaborate, and smash (or elegantly solve) problems together. We’re on a quest to empower live communities, so if this sounds good to you, see what we’re up to on LinkedIn and X , and discover the projects we’re solving on our Blog . Be sure to explore our Interviewing Guide to learn how to ace our interview process. About the Team Twitch Security Platform builds and operates the foundational software, data, and automation that enable security at scale across Twitch. As a Software Development Engineer II (SDE II) on the Security Platform team, you will design, build, and operate critical services, pipelines, and tooling that power Twitch's security, privacy, and compliance programs. About the Role Twitch Security Platform builds and operates the foundational software, data, and automation that enable security at scale across Twitch. As a Software Development Engineer II (SDE II) on the Security Platform team, you will design, build, and operate critical services, pipelines, and tooling that power Twitch's security, privacy, and compliance programs. In this role, you will work at the intersection of software, security, privacy, and data engineering, contributing production systems that handle large-scale security telemetry, automate security workflows, and provide reliable data and services to internal teams. You will partner closely with engineers and product teams to solve real-world security problems through well-designed software. You will own projects end-to-end from design and implementation through deployment and operational support for the systems that are business-critical and highly visible. The problems yo

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! We’re looking for a Research Scientist to advance how high-quality data and environments for AI agents are created. You’ll build and optimize pipelines that combine real-world data, automated generation, and human expert input. Working with domain experts, academic partners, customers, and our product and engineering teams, you’ll scale these pipelines to target frontier model performance gaps and expand data and environment diversity. Your work will amplify human knowledge and judgement, enabling experts to create and refine data and agentic environments that strengthens Snorkel’s position as the frontier data lab. This role is ideal for someone who wants to advance frontier AI through data and environment creation and enjoys turning research into reusable, scalable systems. Location: San Francisco, New York, OR REMOTE Main Responsibilities Design, implement, and optimize reusable pipelines that combine AI capabilities with expert judgment to accelerate data and agentic environment creation. Design and run rigorous experiments to validate proof-of-concept approaches, measure their impact on data quality, pipeline efficiency, and model performance, and communic

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! About the Role Snorkel AI is looking for a Head of Talent Acquisition Operations & Insights to build and lead the systems, processes, tools, metrics, and operational infrastructure that power our recruiting organization. This leader will own the design and execution of a modern TA operations function that enables Snorkel AI to scale hiring with speed, quality, consistency, and data-driven decision-making. This is a builder role for someone who has stood up TA operations in a hyper-growth technical startup environment. You should be equally comfortable designing the strategy, implementing the systems, improving process, building reporting, leading recruiting coordination, and partnering with recruiting and business leaders to improve how hiring gets done. We are looking for someone who brings strong operational discipline, deep knowledge of recruiting systems and workflows, and a forward-looking perspective on how AI can modernize talent acquisition. What You’ll Do Build and lead the TA operations function for Snorkel AI, including recruiting systems, tools, workflows, reporting, process, and coordination. Own the recruiting tech stack, including ATS configu

Software is eating the world, but AI is eating software. We live in unprecedented times – AI has the potential to exponentially augment human intelligence. Every person will have a personal tutor, coach, assistant, personal shopper, travel guide, and therapist throughout life. As the world adjusts to this new reality, leading platform companies are scrambling to build LLMs at billion scale, while large enterprises figure out how to add it to their products. To make them safe, aligned and actually useful, these models need human evaluation and reinforcement learning through human feedback (RLHF) during pre-training, fine-tuning, and production evaluations. This is the main innovation that’s enabled ChatGPT to get such a large headstart among competition. At Scale, our products include the Generative AI Data Engine, SGP, Donovan, and others that power the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI. At the foundation of these products is the Platform Engineering team. In this role, you will lead the design and development of core data storage, streaming, caching, and indexing platforms and underlying systems. You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies. You will: Drive the architecture, design, implementation, and reliability of our foundational data platforms and systems, working closely with stakeholders and internal customers to understand and refine requirements. Collaborate with cross-functional teams to define, design, and deliver new features. Proactively identify opportunities for, and driving improvements to, current programming practices, including process enhancements and tool upgrades. Present technical information to teams and stakeholders, providing

Software is eating the world, but AI is eating software. We live in unprecedented times – AI has the potential to exponentially augment human intelligence. Every person will have a personal tutor, coach, assistant, personal shopper, travel guide, and therapist throughout life. As the world adjusts to this new reality, leading platform companies are scrambling to build LLMs at billion scale, while large enterprises figure out how to add it to their products. To make them safe, aligned and actually useful, these models need human eval and reinforcement learning through human feedback (RLHF) during pre-training, fine-tuning, and production evaluations. This is the main innovation that’s enabled ChatGPT to get such a large headstart among competition. At Scale, our products include the Generative AI Data Engine, SGP, Donovan, and others that power the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI. At the foundation of these products is the Platform Engineering team. In this role, you will support the design and development of shared platforms used across Scale. This includes designing our foundational data platforms and lifecycle, architecting Scale’s core cloud infrastructure and orchestration stack, and redefining how engineers develop, build, test, and deploy software at Scale. You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies. You will: Drive the design, and implementation of our foundational platforms and systems, working closely with stakeholders and internal customers to understand and refine requirements. Collaborating with cross-functional teams to define, design, and deliver new features. Proactively identifying opportunities for, and driving improvements to, current p

Software is eating the world, but AI is eating software. We live in unprecedented times – AI has the potential to exponentially augment human intelligence. Every person will have a personal tutor, coach, assistant, personal shopper, travel guide, and therapist throughout life. As the world adjusts to this new reality, leading platform companies are scrambling to build LLMs at billion scale, while large enterprises figure out how to add it to their products. To make them safe, aligned and actually useful, these models need human eval and reinforcement learning through human feedback (RLHF) during pre-training, fine-tuning, and production evaluations. This is the main innovation that’s enabled ChatGPT to get such a large headstart among competition. At Scale, our products include the Generative AI Data Engine, SGP, Donovan, and others that power the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI. At the foundation of these products is the Identity Engineering team. In this role, you will help support the design and development of core software systems specifically focused on identity, access management, authorization, and authentication. You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies. You will: Drive the design, and implementation of our identity infrastructure to ensure secure authentication and authorization across enterprise systems. Build software for authentication mechanisms such as Single Sign-On (SSO), Multi-Factor Authentication (MFA), and federated identity solutions (SAML, OAuth, OpenID Connect). Build software for authorization mechanisms such as Relation-based access control (ReBAC), Attribute-based access control (ABAC), Role-based access cont

Software is eating the world, but AI is eating software. We live in unprecedented times – AI has the potential to exponentially augment human intelligence. Every person will have a personal tutor, coach, assistant, personal shopper, travel guide, and therapist throughout life. As the world adjusts to this new reality, leading platform companies are scrambling to build LLMs at billion scale, while large enterprises figure out how to add it to their products. To make them safe, aligned and actually useful, these models need human eval and reinforcement learning through human feedback (RLHF) during pre-training, fine-tuning, and production evaluations. This is the main innovation that’s enabled ChatGPT to get such a large headstart among competition. At Scale, our products include the Generative AI Data Engine, SGP, Donovan, and others that power the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI. At the foundation of these products is the Identity Engineering team. In this role, you will help support the design and development of core software systems specifically focused on identity, access management, authorization, and authentication. You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies. You will: Drive the design, and implementation of our identity infrastructure to ensure secure authentication and authorization across enterprise systems. Build software for authentication mechanisms such as Single Sign-On (SSO), Multi-Factor Authentication (MFA), and federated identity solutions (SAML, OAuth, OpenID Connect). Build software for authorization mechanisms such as Relation-based access control (ReBAC), Attribute-based access control (ABAC), Role-based access cont

Software is eating the world, but AI is eating software. We live in unprecedented times – AI has the potential to exponentially augment human intelligence. Every person will have a personal tutor, coach, assistant, personal shopper, travel guide, and therapist throughout life. As the world adjusts to this new reality, leading platform companies are scrambling to build LLMs at billion scale, while large enterprises figure out how to add it to their products. To make them safe, aligned and actually useful, these models need human eval and reinforcement learning through human feedback (RLHF) during pre-training, fine-tuning, and production evaluations. This is the main innovation that’s enabled ChatGPT to get such a large headstart among competition. At Scale, our products include the Generative AI Data Engine, SGP, Donovan, and others that power the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI. At the foundation of these products is the Platform Engineering team. In this role, you will support the design and development of shared platforms used across Scale. This includes designing our foundational data platforms and lifecycle, architecting Scale’s core cloud infrastructure and orchestration stack, and redefining how engineers develop, build, test, and deploy software at Scale. You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies. You will: Drive the design, and implementation of our foundational platforms and systems, working closely with stakeholders and internal customers to understand and refine requirements. Collaborating with cross-functional teams to define, design, and deliver new features. Proactively identifying opportunities for, and driving improvements to, current p

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. AI will transform every business, but we’re still just scratching the surface of its potential. Its true power lies in its ability to automate the often overlooked workflows that are the lifeblood of organizations. At Airtable, we are evolving into an AI-native platform, and we have the unique opportunity to provide AI tools that are deeply embedded within a team’s data and workflows. We’re looking for a talented senior design leader to join our team and help guide this transformation by driving the creation of new experiences. How might AI transform user intent into data schema, workflows, and interfaces? How do we give users meaningful control when automation is doing work on their behalf? How do we design complex, multi-step experiences that feel simple? If you’re ready to dig into these questions with a crew of humble, talented, and deeply thoughtful designers, we can't wait for you to apply. You’ll be an integral part of a collaborative team, contributing to both strategic vision and design execution. What you'll do Craft exceptional experiences Using your full range of product design skills to discover, design, and deliver intuitive, well-crafted experiences. You’ll elevate some Airtable’s most critical workflows while holding a high bar for overall design quality. Contribute to a vision of Airtable The platform is evolving rapidly and we want you to help define a strong point of view about where we are going. You’ll shape not just features but the broader arc of how Airtable grows. We are committed to becoming an AI-native platform, and we’re looking for a designer to help steer this evolution and shape how these new capabilities integrate into the core user experience. Experiment with AI-assisted proto

About the Team We’re looking for a Senior University Recruiter to help us identify and attract top-tier early career talent to join our Engineering and Design teams. For the first time, our global organizations of DoorDash, Wolt, and Deliveroo will be joining forces for one unified, global internship program and you would be on the forefront of building what this strategy looks like for a global team. From building relationships with universities to advising on the interview processes, being a part of headcount conversations to planning events and running performance review cycles, you will help build the foundations of this program making it something that can scale and grow each year. About the Role Your impact will go beyond filling roles; you’ll shape how we approach hiring from how we define what ‘great’ looks like in an engineer. You’ll play a key role in how we build diverse talent pipelines and create a seamless experience for every candidate and intern throughout the program. You’ll be the bridge between us and top university talent, helping DoorDash continue to invest in, build, and grow the next generation. This role sits within our Engineering Recruiting team and reports into the Recruiting Manager for Global University Recruiting. It will be based in San Francisco, CA. You’re Excited About This Opportunity Because You Will… Manage full-cycle recruitment for all technical intern and new grad hiring roles across the US Identify, engage, and maintain relationships with high-potential candidates, partnership organizations, and universities Build diverse talent pipelines, and run smooth, efficient processes from first conversation to final offer Embed DE&I principles into every stage of the process from diversifying sourcing channels to reducing bias in assessment and ensuring diversity in interview panels. Build and streamline interview processes and workflows ensuring we’re iterating and adjusting as we scale and grow Train interviewers and coach

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 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

AI only answers correctly when it can trust the data underneath it. This role owns two connected parts of how Sigma shows up in that world: where Sigma's experience lives outside its own product (MCP, a CLI, the Claude and ChatGPT marketplaces, integrations like Slack, Teams, and Glean), and the semantic layer that makes every one of those surfaces trustworthy. The first mandate is Sigma's AI ecosystem: defining Sigma's approach to MCP, giving external agents structured, governed access to Sigma's data model; owning the CLI, giving developers a fast way to work with Sigma outside the UI; and building Sigma's presence in the Claude and ChatGPT marketplaces, plus integrations for Slack, Teams, Glean, and similar surfaces, so people can reach Sigma's data wherever they already work. This is some of the most visible, fastest-growing surface area in the product. The second mandate is the semantic layer underneath it all. Every agent, chat answer, and integration is only as reliable as the data model behind it — get a metric definition wrong here, and every surface built on top inherits the mistake. This includes setting the roadmap for how semantic views connect across data platforms and how the model evolves as new AI capabilities emerge. What you'll do Define Sigma's approach to MCP, giving external agents and tools structured, governed access to Sigma's data model. Own the CLI roadmap, giving developers a fast, scriptable way to work with Sigma outside the UI. Build Sigma's presence in the Claude and ChatGPT marketplaces, along with integrations for Slack, Teams, Glean, and similar surfaces, so people can reach Sigma's data wherever they're already working. Set the roadmap for Sigma's data modeling strategy, including how semantic views connect across data platforms and how the semantic layer evolves as new AI capabilities emerge. Partner with engineering and design to ship integration and semantic modeling capabilities that hold up at enterprise scale.