In Business Risk Manager Vice President New York in San Francisco

You will: Manage the growth program from end to end, including top-of-the-funnel growth / recruiting campaigns, applications processing, and hiring and onboarding Represent and champion the brand, promoting its value proposition to candidates and stakeholders, driving engagement, and taking ownership of process improvements that streamline growth pipelines and support program success Optimize full growth funnel for conversion and experience Build and lead new growth recruiting campaigns and channels to meet business goals Be the subject matter expert for all recruiting systems (ATS: Greenhouse), tools, and processes, and provide training/onboarding as needed Own internal reporting and analytics, and keeping all the internal hiring data clean and up-to-date in our systems Be the strategic driver behind on impactful initiatives to improve the workflow, data infrastructure and reporting Proactively flag discrepancies in hiring plans, interview process, JDs, offer details, etc. and maintain data integrity and operational excellence within the team Work from the San Francisco office, with occasional travel for onsite growth events. Ideally you’d have: Minimum of 3-7 years of experience working in Growth, Recruiting or RecOps at a rapidly growing company Extensive experience using Greenhouse as a Site Admin (user permissions, approvals, custom options) and pulling ad hoc reports using our internal TA tools (report connector, reporting capabilities, and limitations) Strong knowledge of Gsuite (VLOOKUP, pivot tables, data validation, conditional statements and formatting, filters, etc.) Excellent written and verbal communication skills, with the ability to tailor messaging to diverse audiences Must have a deep understanding of Growth / Recruiting Pipelines, Funnels and Conversion metrics Demonstrated excellent project management skills, ability to pull and manipulate data sets, critically analyze existing processes, and identify opportunities for process improvement Able to

About The Team: To help achieve our mission, we are looking for a Recruiting Coordinator to join our team. AI is rapidly changing the world, and Scale is growing to meet that rapid demand. Recruiting Coordinators who join today will help schedule and coordinate interviews, provide exceptional candidate experience, and help develop strategies that will scale alongside the new challenges we’re facing. Many of our greatest challenges are yet to be solved, and we're looking to hire a Recruiting Coordinator who is excited to tackle them. About the Role: We are looking for a talented Recruiting Coordinator on a 6 Month Contract (with possibility of extension or conversion given further business need). This is a hybrid role (3 days per week in office) based in our San Francisco or New York City office to join our team and participate in the hiring process from beginning to end. You’ll be directly working with our hiring partners, recruiters and candidates to create a personal and creative recruiting experience! You will: Schedule, coordinate, and confirm candidate interviews, handling cancellations and reschedules promptly across multiple time zones Collaborate and communicate effectively with recruiters, hiring managers, and business leaders to ensure smooth interview processes Create a welcoming and high-touch candidate experience for both virtual and in-person interviews Support Recruiting Operations on initiatives related to improving coordination workflows, candidate experience and interviewer experience Ideally you have: 1-2 years of relevant experience; scheduling high volume (100+ interview events a week) and tech industry experience are a plus Familiarity with Greenhouse, ModernLoop, or similar ATS/scheduling tools A highly organized and process-driven approach to work, ensuring SLAs are met and work is completed efficiently and accurately A curious and proactive mindset, leveraging AI tools and technology to identify opportunities for process improve

The Public Sector software engineers (SWEs) create the core product building blocks forward-deployed teams use to develop agentic capabilities that function across multiple domains. SWEs responsibilities include building the systems required to ingest and process federal datasets to support real-time decision-making in contested environments. We develop novel agentic enabling capabilities that includes: Create multi-layered guardrails around agents Optimize data retrieval for agents Orchestrate fleets of asynchronous agents Automatically alerts users to deviations in data Illustrating how an agent reached a decision As a Staff Software Engineer, you will orchestrate the implementation of vertical features and horizontal capabilities to include mentoring other engineers on defining requirements with stakeholders and communication tradeoffs of technical implementations on feature and capabilities until they are accepted by the stakeholders. You will: Orchestrate feature implementation across the Federal engineering team to ensure architectural consistency. Define technical strategy for agentic guardrails, explainability, and fleet orchestration. Ensure system reliability and performance across multiple security classifications and network types. Mentor engineers in the process of defining requirements with stakeholders and gathering acceptance. Communicate high-level technical trade-offs and implementation strategies to senior government stakeholders and Scale C-Suite members. Influence the long-term product strategy and technical roadmap for the Federal business unit. Consult on the architecture of AI-powered solutions for large-scale federal contracts. Ideally you will have: Full Stack Development: Proficiency in front-end, back-end development and infrastructure, including experience with modern web development frameworks, programming languages, and databases Cloud-Native Technologies: Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and experience in

About Scale AI At Scale AI, our mission is to accelerate the development of AI applications. For 8 years, Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including generative AI, defense applications, and autonomous vehicles. With our recent Series F round, we’re accelerating the abundance of frontier data to pave the road to Artificial General Intelligence (AGI) and building upon our prior model evaluation work with enterprise customers and governments to deepen our capabilities and offerings for public and private evaluations. About Data Engine Our Generative AI Data Engine powers the world’s most advanced LLMs and generative models through world-class RLHF (Reinforcement Learning with Human Feedback), human data generation, model evaluation, safety, and alignment. The data we produce is some of the most critical work for how humanity will interact with AI. About Our FDE Team Generating high-quality data is the core problem our business solves. We aim to make producing and delivering high-quality data seamless and efficient for operators and customers. Our Team is building customer and operator-specific infrastructure to provide high-quality data with low turnaround time. You'll be exposed to the cutting edge of the Generative AI industry while directly interfacing with the leading model-building organizations in the space, including the top AI research labs and government agencies. Join us in shaping the future of Artificial General Intelligence. As a Forward Deployed Engineer, you'll be at the forefront of providing the critical data infrastructure that powers the most advanced AI models, directly influencing how humanity interacts with AI. You will work with the world’s leading AI companies and government agencies to solve their most complex AI data-related problems. Responsibilities: Drive Impact: Directly contribute to the advancement of AI by delivering critical data solutions for leading AI innovators and

About Scale AI Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with the world's leading enterprises and government organizations to accelerate their AI transformation through frontier AI systems that solve real business problems. Every day, we work with organizations across finance, healthcare, manufacturing, media and telecommunications to build production AI agents that automate complex workflows, help humans, reason over enterprise knowledge, and operate safely at scale. The Opportunity Applied AI is moving faster than ever. New foundation models, reasoning techniques, agent architectures, and research papers emerge every week. Yet building AI systems that reliably solve real-world problems remains one of the hardest engineering challenges. As a Frontier Agent Engineer (Applied AI) , you'll bridge the gap between cutting-edge AI research and production deployment. You'll work directly with enterprise customers to design, evaluate, and deploy intelligent systems that combine frontier models with structured knowledge, retrieval, traditional machine learning, and enterprise software. Unlike traditional ML roles that focus on a single model or product, you'll work across a diverse portfolio of AI challenges spanning multiple industries and use cases. You may build a multi-agent research system and then participate in designing a customer intelligence platform, a healthcare copilot, or an autonomous workflow for a Fortune 100 company. If you enjoy reading new AI papers, experimenting with the latest models, and shipping production systems that create measurable business impact, you'll fit right in. What You'll Build Frontier AI Systems Design and deploy production AI agents that leverage the latest advances in large language models, reasoning, retrieval, memory, and tool use. Architect intelligent systems that combine LLMs, traditional machine learning, structured knowledge, enterprise data

The Public Sector software engineers (SWEs) create the core product building blocks forward-deployed teams use to develop agentic capabilities that function across multiple domains. SWEs responsibilities include building the systems required to ingest and process federal datasets to support real-time decision-making in contested environments. We develop novel agentic enabling capabilities that includes: Create multi-layered guardrails around agents Optimize data retrieval for agents Orchestrate fleets of asynchronous agents Automatically alerts users to deviations in data Illustrating how an agent reached a decision As a Software Engineer, you will own the development of a vertical feature or a horizontal capability to include defining requirements with stakeholders and implementation until it is accepted by the stakeholders. You will: Design and implement scalable backend systems for Federal customers using cloud-native AI infrastructure. Build features for agentic systems including multi-layered guardrails and data retrieval optimization. Develop data pipelines and machine learning infrastructure to make data sources accessible by agents. Collaborate with cross-functional teams to execute backend solutions for secure environments. Participate in customer engagements to understand requirements and deliver technical solutions. Define requirements with stakeholders and implement features until they are accepted. Contribute to the platform roadmap and product strategy for the Federal business. Ideally you will have: Full Stack Development: Proficiency in front-end, back-end development and infrastructure, including experience with modern web development frameworks, programming languages, and databases Cloud-Native Technologies: Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and experience in developing and deploying applications in a cloud-native environment. Understanding of containerization (e.g., Docker) and container orchestration (e.g., Kubernetes

About Scale At Scale AI, our mission is to accelerate the development of AI applications. For 8 years, Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including: generative AI, defense applications, and autonomous vehicles. With our recent Series F round, we’re accelerating the abundance of frontier data to pave the road to Artificial General Intelligence (AGI), and building upon our prior model evaluation work with enterprise customers and governments, to deepen our capabilities and offerings for both public and private evaluations. About Data Engine Our Generative AI Data Engine powers the world’s most advanced LLMs and generative models through world-class RLHF (Reinforcement Learning with Human Feedback), 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. Our Approach As part of the interview process, you’ll be considered for opportunities across several teams within the GenAI Engineering organization, based on your interests, expertise, and business needs. Potential team placements include Allocation, Growth, Frontier Data, Trust & Safety, Pay, Operator, or Tasking Experience. Together, these teams power Scale’s AI data operations - from building high-impact datasets that push the boundaries of LLM capabilities, to optimizing contributor onboarding and incentives, to safeguarding data integrity through advanced trust, safety, and security measures. They work at the intersection of ML, operations, and analytics to ensure we deliver the highest-quality data at scale. Responsibilities: Design, build, and maintain robust, scalable systems across the full stack, including front-end, back-end, and infrastructure layers Implement high-impact features using modern technologies such as TypeScript, React, Node.js, MongoDB, Elasticsearch, and Temporal Collaborate closely with internal operators (your use

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 Scale AI Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with the world's leading enterprises and government organizations to accelerate their AI transformation through frontier AI systems that solve real business problems. Every day, we work with organizations across finance, healthcare, manufacturing, media and telecommunications to build production AI agents that automate complex workflows, help humans, reason over enterprise knowledge, and operate safely at scale. The Opportunity Applied AI is moving faster than ever. New foundation models, reasoning techniques, agent architectures, and research papers emerge every week. Yet building AI systems that reliably solve real-world problems remains one of the hardest engineering challenges. As a Senior Frontier Agent Engineer (Applied AI) , you'll bridge the gap between cutting-edge AI research and production deployment. You'll work directly with enterprise customers to design, evaluate, and deploy intelligent systems that combine frontier models with structured knowledge, retrieval, traditional machine learning, and enterprise software. Unlike traditional ML roles that focus on a single model or product, you'll work across a diverse portfolio of AI challenges spanning multiple industries and use cases. You may build a multi-agent research system and then participate in designing a customer intelligence platform, a healthcare copilot, or an autonomous workflow for a Fortune 100 company. If you enjoy reading new AI papers, experimenting with the latest models, and shipping production systems that create measurable business impact, you'll fit right in. What You'll Build Frontier AI Systems Design and deploy production AI agents that leverage the latest advances in large language models, reasoning, retrieval, memory, and tool use. Architect intelligent systems that combine LLMs, traditional machine learning, structured knowledge, enterpri

About the Team Data is at the foundation of DoorDash success. The Data Engineering team builds database solutions for various use cases including reporting, product analytics, marketing optimization and financial reporting. By implementing pipelines, data structures, and data warehouse architectures; this team serves as the foundation for decision-making at DoorDash. About the Role DoorDash is looking for a Softare Engineer II to be a technical powerhouse to help us scale our data infrastructure, automation and tools to meet growing business needs. You're excited about this opportunity because you will… Work with business partners and stakeholders to understand data requirements Work with engineering, product teams and 3rd parties to collect required data Design, develop and implement large scale, high volume, high performance data models and pipelines for Data Lake and Data Warehouse Develop and implement data quality checks, conduct QA and implement monitoring routines Improve the reliability and scalability of our ETL processes Manage a portfolio of data products that deliver high-quality, trustworthy data Help onboard and support other engineers as they join the team We're excited about you because… 3+ years of professional experience working in data engineering, business intelligence, or a similar role You have proficiency in using AI coding tools (e.g., Claude Code, Codex, Cursor) in the full software development lifecycle, including designing, generating code, testing, monitoring and releasing software Proficiency in programming languages such as Python/Java 3+ years of experience in ETL orchestration and workflow management tools like Airflow, Flink, Oozie and Azkaban using AWS/GCP Expert in Database fundamentals, SQL and distributed computing 3+ years of experience with the Distributed data/similar ecosystem (Spark, Hive, Druid, Presto) and streaming technologies such as Kafka/Flink. Experience working with Snowflake, Redshift, PostgreSQL and/or other DBMS

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 running frontier open-weight LLMs and VLMs (such as GLM, Qwen, Kimi, and DeepSeek) ourselves — real-time GPU serving, high-throughput batch inference, and fine-tuning on autoscaling GPUs — delivering large cost and latency wins (for example, a billion embeddings produced roughly 20× cheaper and visual models served roughly 72% cheaper). We also own core platform surfaces including the LLM Gateway, Agent Gateway, evals infrastructure, guardrails, and cost attribution. About the Role You will join a small, high-leverage team building production infrastructure for Generative AI at DoorDash, leading the design and architecture of our open-weights model platform spanning inference and fine-tuning: real-time GPU serving, high-throughput batch inference, and model fine-tuning. You’ll set technical direction across model serving and inference engines, fine-tuning and training pipelines, GPU autoscaling and utilization, batch pipelines, backend services, and observability, and mentor engineers as you go. This role is ideal for a senior engineer who enjoys owning ambiguous, high-impact systems and pushing the cost/performance frontier of GPU inference and fine-tuning in a fast-moving technical area where product needs, model capabilities, vendor ecosystems, and cost/performance tradeoffs are evolving quickly. You’re excited about this opportunity because you will… Lead the design of infrastructure that helps DoorDash teams move GenAI ideas from prototype to production, increasing the velocity of business impact from AI across the company. Own and evolve our open-weights serving stack — real-time GPU endpoints, high-thr

About the Team AI Research Lab is one of DoorDash’s frontier innovation hubs, focused on building the foundation for an AI-native future across our three core audiences: consumers, merchants, and dashers. As AI capabilities accelerate, the AI Research Lab operates at the center of technical exploration and real-world execution — connecting frontier model research, internal platform investments, operator teams, and strategic external partners. Our mission is to translate cutting-edge AI research into scalable, production-ready systems that drive measurable business impact. We combine deep technical rigor with strong operational execution to ensure that breakthrough capabilities become durable competitive advantages for DoorDash. About the Role As an Associate Manager, Strategy & Operations on our AI Research Lab, you will play a central role in converting frontier AI advancements into shipped products and scalable infrastructure. You will operate across research, product, and operations to move from early discovery and experimentation to deployment and impact. This role sits at the intersection of customer insight, technical innovation, and business execution. You will help define and scale the Lab’s most important bets while building the foundations that enable AI applications to compound over time. You’re Excited About This Opportunity Because You Will … Reimagining core experiences through AI, such as the merchant journey, by partnering directly with in-field merchants, sales, support, product, and engineering teams. You will help unify major initiatives into a coherent, AI-native interaction model. Own revenue-driving AI initiatives, operating as the accountable business owner for high-priority AI bets and ensuring clear linkage between technical progress and financial outcomes. Lead business planning cycles, developing go-to-market strategies for AI-powered products and capabilities, overseeing execution through structured project plans, resource allocation,

About the Team The Analytics team is looking for Data Scientists to guide measurement, strategy, and tactical decision-making using Advanced Analytics approaches, as we expand our platform across the globe. Data Scientists at DoorDash work to uncover insights and turn them into actionable recommendations, helping drive decisions for the entire organisation. Analytics is very integral to all operational areas at DoorDash. About the Role Data Science at DoorDash involves diving deeper into our data to solve crucial business problems, ideate & run experiments to solve for insights gleaned from this deep dive and work with a cross-functional team to drive real-world operational change. This is a rare operational and actionable data-driven experience. We solve many exciting challenges from all three sides of our marketplace including customer acquisition, balancing supply and demand, fraud and support, marketing, marketplace efficiency, and more. If you enjoy finding patterns amidst chaos, are excited to build a market from 0 to 1, and have experience using analytics to affect revenue, growth, operations or beyond, we're looking for someone like you! You're excited about this opportunity because you will… As a senior Individual Contributor, mentor and influence junior Data Scientists in investigating complex issues and uncovering key drivers of our business 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 8+ years of experi

About the Team Data is at the foundation of DoorDash success. The Data Engineering team builds database solutions for various use cases including reporting, product analytics, marketing optimization and fi nancial reporting. Team serves as the foundation for decision-making at DoorDash. About the Role DoorDash is looking for a Sta ff Software Engineer,Data to be a technical lead and help architect and scale our data reliability, data infrastructure, automation and tools to meet growing business needs. You’re excited about this opportunity because you will... Own critical data systems that support multiple products/teams Develop, implement and enforce best practices for data infrastructure and automation Design, develop and implement large scale, high volume, high performance data models and pipelines for Data Lake and Data Warehouse Improve the reliability and scalability of our Ingestion, data processing, ETLs, Reporting tools and data ecosystem services Manage a portfolio of data products that deliver high-quality, trustworthy data Help onboard and support other engineers as they join the team We’re excited about you because... 8+ years of professional experience as a hands-on engineer and technical leader leading multiple projects 6+ years experience working in data platform and data engineering or a similar role You have proficiency in using AI coding tools (e.g., Claude Code, Codex, Cursor) in the full software development lifecycle, including designing, generating code, testing, monitoring and releasing software Pro fi ciency in programming languages such as Python/Kotlin/Scala 4+ years of experience in ETL orchestration and work fl ow management tools like Air fl ow Expert in database fundamentals, SQL, data reliability practices and distributed computing 4+ years of experience with the Distributed data/similar ecosystem (Spark, Presto) and streaming technologies such as Kaa/Flink/Spark Streaming Excellent communication skills and experience working

About the Team The CPG Ad Sales Team is responsible for the marketing vision, development, and growth of our advertising partnerships. This team is rapidly growing, and is seeking additional team members to build an industry-leading ads and promotions business across DoorDash’s CPG offerings. The growing DoorDash ads business has quickly become the single best place for merchants and brands to market to local customers, in an ecosystem that benefits all parties. About the Role As the Industry Manager, CPG, you will lead a team of Account Executives and Post Sales Managers to build partnerships that create tangible value for both advertisers and DoorDash. In this role, you will manage the ads strategy across a portfolio of CPG brands (may include subcategories of alcohol, personal care, household, beverages, sweets, snacks, pantry, fresh, frozen, pets), and drive adoption of our growing ads and promotions offering. You will work cross-functionally with strategy, operations, marketing, analytics, and product, to innovate on our future approach and solutions. You will report into the Head of CPG Advertising Sales, in our Sales & Business Development organization. You’re excited about this opportunity because you will… Successfully lead and develop a team of Account Executives and Post Sales Managers to consistently exceed business growth and product/feature adoption goals, grow advertiser value, and drive sustainable revenue for DoorDash Establish trusted senior level customer relationships and deliver thought leadership both internally and externally in the CPG industry Represent advertiser needs to influence our Ads & Promos product roadmap and go to market strategy Develop sales materials and sales processes to enable future scale of the team and business Develop annual and quarterly sales plans and analyses to achieve ambitious goals and and help customers meet their business and marketing objectives We’re excited about you because… You ha