Ai Knowledge Analyst in San Francisco

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

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 role The world is moving fast — and AI is moving faster. As a Product Marketing Manager focused on AI at Sigma, you'll be at the tip of the spear, helping define how we tell the story of one of the most exciting areas of the product. This role is as much about clarity as it is about creativity: you'll take complex, fast-evolving AI capabilities and distill them into the market messages, sales narratives, and customer stories that make people say "I get it — and I want it." We're looking for someone with genuine intellectual curiosity about AI, a bias for action, and exceptional instincts for what makes a message land. If you can absorb a lot of information quickly, find the signal in the noise, and write messaging that moves people — this role is for you. What you'll do Develop and refine positioning and messaging for Sigma's AI features, working closely with the Director of Product Marketing, AI and the Product team. Create sales enablement content — one-pagers, battlecards, demo guides, and objection handlers — that help the field confidently sell Sigma's AI capabilities. Support product launches for AI features: coordinate across product, design, marketing, and sales to bring new capabilities to market clearly and effectively. Research competitors' AI positioning and identify opportunities to sharpen Sigma's differentiation. Write and contribute to thought leadership content, blog posts, and customer-facing collateral that educate the market on Sigma's AI vision. Gather and synthesize customer and prospect insights — from win/loss data, customer interviews, and sales calls — to continuously improve messaging. Partner with demand generation and content teams to ensure AI messaging is consistently represented across campaigns, website, and events. What we're looking for 3+ years of product marketing experience in B2B enterprise software and/or cloud data platforms. The ability to learn quickly and deeply — you can get up to speed on a new te

Role Summary Scale builds AI applications for organizations where reliability, security, and measurable results matter. Our core platform, SGP, gives teams the capabilities to build, deploy, evaluate, and operate those applications in customer environments. We're looking for a product leader to own the strategy and roadmap for SGP's core platform and lead the PM team responsible for it. You will work with customers, platform engineering, and forward deployed teams to build capabilities customers need, productize work developed in the field when it has broader value, and improve how teams build, deploy, and operate AI applications. This is a hands-on leadership role. You will connect work across teams into a coherent product, make difficult scope and investment decisions, and stay close enough to the details to know whether what we ship works for the people using it. What you'll do Own the platform strategy and roadmap. Prioritize across developer experience, capabilities customers need, and productizing work built in the field where it has broader value. Sequence investments against customer value, commitments, and dependencies. Define how the product should work. Work with users and engineers to write clear requirements and vibe code prototypes, user journeys, and measure success through customer outcomes, capability adoption, delivery time, and production performance, and follow through on gaps after launch. Align teams across the business. Work with platform engineering, forward deployed PMs, and business leaders to agree on shared capabilities, rollout priorities, and necessary differences across environments. Make clear what is available, where it works, and what remains to be delivered. Build and lead a strong PM team. Establish clear ownership across related product areas, hire and coach PMs, and raise the quality of product thinking and written requirements. Stay directly involved in the most consequential decisions. What we're looking for A track record of

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

We are seeking an experienced and detail-oriented US Payroll Specialist to oversee our end-to-end multi-state payroll operations. In this role, you will ensure accurate, timely, and compliant payroll processing for all US-based employees while managing internal payroll initiatives. The ideal candidate is a strategic problem-solver with deep expertise in US labor laws, taxation, and ADP+Workday payroll systems. You will: Full-Cycle Payroll Processing: Oversee the accurate and timely processing of multi-state bi-weekly and semi-monthly payrolls for over a thousand exempt and non-exempt employees across most of the USA. Compliance & Taxation: Ensure strict adherence to federal, state, and local tax laws, as well as FLSA regulations. Monitor regulatory changes and update internal systems accordingly. Year-End Processing: Manage year-end payroll activities, including W-2 and W-2c generation, fringe benefit reporting, and annual tax reconciliations. Cross-Functional Collaboration: Partner closely with HR to ensure accurate data flow for onboarding, offboarding, benefits deductions, and compensation changes. Ability to work with Accounting to ensure accurate general ledger mapping, month-end close procedures, and payroll account reconciliations. System Administration & Optimization: Act as the primary subject matter expert for our payroll system (e.g., Workday, ADP). Identify bottlenecks, recommend process improvements, and lead system upgrades or implementations. Issue Resolution, Continuous Improvement & Auditing: Conduct regular audits of payroll data to identify and resolve discrepancies. Serve as the ultimate point of continuous improvement with AI and other methodologies to ensure Scale’s payroll processes are best in class. Ideally you'd have: 5+ years of payroll experience. Strong organizational skills; the ability to get all priority tasks completed by the end of each day. Confidentiality and integrity. Accuracy under pressure and extreme attention to

At Scale, we are driving the future of AI and Machine Learning across a variety of industries. As the Program Manager for Compliance, you will play a pivotal role in the continued success of Scale. Your role will be instrumental in ensuring the effective operation of our Compliance department and our GRC function, allowing us to maintain the highest standards in our industry. Reporting to the Director & Associate General Counsel, Compliance, you will be a dedicated program manager for Scale's enterprise compliance program and the person who turns policy into practice across anti-bribery and anti-corruption, gifts and entertainment, conflicts of interest, third-party risk and sanctions, policy lifecycle, and company-wide training. This is a hands-on builder, not a maintenance role. You will support Commercial, Public Sector, and international business lines, working closely with Legal, Procurement, Finance, Security, and go-to-market teams. You will: Help build, design, improve, and streamline Scale's core compliance programs, including anti-bribery and anti-corruption (ABAC), gifts and entertainment, conflicts of interest, and third-party risk and sanctions screening. Collaborate with stakeholders across the company to improve compliance policies, processes, and procedures. Monitor regulatory developments relevant to Scale's business, translate them into concrete policy and process changes, and track compliance obligations flowing out of customer contracts. Partner with leadership to build, mature, and operationalize the company's enterprise risk management (ERM) framework, identifying and assessing key business risks. Build the reporting layer: metrics and periodic reporting that give Legal & GRC leadership a defensible picture of program health. Flex into audit and assurance work during peak certification periods, and own inbound customer and investor compliance diligence questionnaires. Ideally you'd have: 5+ years building or operating ethics and c

At Scale, we develop reliable AI systems for the world’s most important decisions. Scale’s product marketing team is responsible for developing and executing strategies that drive awareness and engagement for Scale’s offerings amongst our core audiences. We take a data-driven approach to understand our customers’ needs and challenges, ensuring that their voices are reflected in product development and messaging. We partner closely with product, engineering, research, sales, comms, and the broader marketing team to create a cohesive customer experience across all our channels. We aim to provide valuable insights and resources that help our customers execute on their AI transformation journey. This role will focus on developing and optimizing vertical-specific messaging and content for Scale’s applications business to ensure our messaging resonates with core buyers across verticals. The ideal candidate combines strategic thinking with hands-on execution. You will: Develop clear, compelling messaging for enterprise offerings tailored to key personas within target verticals Create marketing assets, including slide decks, videos, blog posts, and one-pagers, that effectively communicate our value propositions to vertical leaders and support our sales team’s pursuits Lead positioning and sales enablement efforts to drive awareness and engagement for Scale’s offerings. Drive cross-functional marketing programs around target verticals, in conjunction with product, engineering, sales, and growth marketing to create a cohesive customer experience and contribute to pipeline targets Collaborate with field marketing and events teams to develop vertical-specific event strategies, content, and experiences that drive engagement within customer and target accounts Drive customer marketing efforts, creating both strategy and tactics to maximize the value Scale and customers get from our shared success, including case studies, testimonials, visual assets and event particip

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

Scale Labs, Research Scientist — Agent Robustness As the leading data and evaluation partner for frontier AI companies, Scale plays an integral role in understanding the capabilities and safeguarding AI models and systems. Building on this expertise, Scale Labs has launched a new team focused on policy research, to bridge the gap between AI research and global policymakers to make informed, scientific decisions about AI risks and capabilities. Our research tackles the hardest problems in agent robustness, AI control protocols, and AI risk evaluations to help governments, industry, and the public understand and mitigate AI risk while maximizing AI adoption. This team collaborates broadly across industry, the public sector, and academia and regularly publishes our findings. We are actively seeking talented researchers to join us in shaping this vision. As a Research Scientist working on Agent Robustness you will work on the fundamental challenges of building AI agents that are safe and aligned with humans. For example, you might: Research the science of AI agent capabilities with a focus on how they relate to safety, risk factors, and methodologies for benchmarking them; Design and build harnesses to test AI agents’ tendency to take harmful actions when pressured to do so by users or tricked into doing so by elements of their environment; Design and build exploits and mitigations for new and unique failure modes that arise as AI agents gain affordances like coding, web browsing, and computer use; Characterize and design mitigations for potential failure modes or broader risks of systems involving multiple interacting AI agents. Ideally you’d have: Commitment to our mission of promoting safe, secure, and trustworthy AI deployments in the industry as frontier AI capabilities continue to advance. Practical experience conducting technical research collaboratively. You should be comfortable building and leveraging agent scaffolding, designing evaluation harnesses, an

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

Scale's LLM post-training platform team builds our internal distributed framework for large language model training. The platform powers MLEs, researchers, data scientists, and operators for fast and automatic training and evaluation of LLMs. It also serves as the underlying training framework for the data quality evaluation pipeline. Scale is uniquely positioned at the heart of the field of AI as an indispensable provider of training and evaluation data and end-to-end solutions for the ML lifecycle. You will work closely with Scale’s ML teams and researchers to build the foundation platform which supports all our ML research and development works. You will be building and optimizing the platform to enable our next generation LLM training, inference and data curation. If you are excited about shaping the future AI via fundamental innovations, we would love to hear from you! You will: Build, profile and optimize our training and inference framework. Collaborate with ML and research teams to accelerate their research and development, and enable them to develop the next generation of models and data curation. Research and integrate state-of-the-art technologies to optimize our ML system. Ideally you’d have: Passionate about system optimization Experience with multi-node LLM training and inference Experience with developing large-scale distributed ML systems Experience with post-training methods like RLHF/RLVR and related algorithms like PPO/GRPO etc. Strong software engineering skills, proficient in frameworks and tools such as CUDA, Pytorch, transformers, flash attention, etc. Strong written and verbal communication skills to operate in a cross functional team environment. Nice to haves: Demonstrated expertise in post-training methods and/or next generation use cases for large language models including instruction tuning, RLHF, tool use, reasoning, agents, and multimodal, etc. Compensation packages at Scale for eligible roles include base salary, equity,

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

We are building the Finance team to help make data-driven and financially sound decisions for Scale. The team is responsible for improving strategic, financial, and operational decisions by partnering with the leadership team in making critical decisions across Scale. The Corporate Finance team is responsible for owning the company’s budget, helping to drive monthly forecasts and annual planning processes, allocating and deploying the company’s resources efficiently, and performing financial analyses in partnership with all departments. As AI reshapes the competitive landscape, Corporate Finance sits at the center of decisions about where Scale invests, how quickly we scale, and which bets we make. You will have a unique opportunity to work closely with department heads on real-time, high-priority business issues and use quantitative insights to drive better decision making across Scale. The ideal candidate will not only have the technical skills to support their recommendations but also strong interpersonal skills to manage various stakeholders. What You’ll Do Provide analysis to support short and long-term decisions regarding workforce planning across the company. Own tools (such as the company's workforce planning system, TeamOhana) to automate and streamline reporting and headcount processes Partner cross-functionally with HR, Recruiting, Compensation, and Analytics teams to drive scalable analyses and insights. Define and maintain KPIs to measure impact on strategic initiatives and resource allocation. Manage the development, implementation, and administration of our financial forecasting system (Pigment) Partner with finance and accounting to drive process improvements (e.g. month-end close and reporting) Implement enhancements to forecasting tools, processes, and reporting deliverables that reduce manual work and improve data integration Support management, Board business, and financial planning, including presentations and key analysis requests Help execute

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