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About the role Every enterprise is racing to build AI-powered apps and agents but speed without the right runtime creates chaos, not transformation. Sigma is the AI Runtime Environment that makes those apps governable, scalable, and real, and the Sr. PMM, Sigma Apps will play a critical role in developing and executing the go-to-market narrative and strategy for Sigma Apps. This role requires someone who understands both sides of the enterprise software conversation: the IT leaders and data engineers who evaluate and govern application infrastructure, and the line-of-business owners who care about outcomes, speed, and usability. You'll translate Sigma's application development capabilities into stories that resonate with both and create the materials the sales team needs to tell those stories in the field. What you'll do Develop and maintain positioning and messaging for Sigma Apps including no-code app building, AI-assisted workflow automation, embedded analytics, and apps built with external coding agents working closely with the Director of Product Marketing, Apps and the Product team. Support new feature launches and capability expansions, coordinating across product, design, marketing, and sales to bring new capabilities to market clearly and effectively. Work closely with Product and Engineering to deeply understand and influence the Sigma Apps roadmap bringing market, customer, and competitive insights that help shape and prioritize it. Partner with sales reps and the Enablement team to understand what's working in the field and use those insights to sharpen messaging, update battlecards, and improve enablement materials. Partner with the Enablement team to build and maintain sales enablement content solution briefs, pitch decks, use case guides, competitive comparisons, and discovery question frameworks that help the field confidently sell Sigma Apps Build and maintain competitive analysis and battlecards for the no-code/low-code, embedded anal

About This Role This is not your average Account Executive role. At Sigma, we believe that people are our most valuable resource, and so we relentlessly invest in our team. Account Executives are set up to thrive while generating meaningful pipeline, winning new customers, and directly contributing to the success of our organization. Working with Sigma gives you the opportunity to get in on the ground floor of a high-growth startup. Our Account Executives are crucial for growing our customer base and our company, making this one of Sigma’s most critical roles. Who You Are: A go-getter who is hungry for personal growth and career advancement Someone who understands the power and value of data in driving innovation and business initiatives Someone who is principled, honest, humble, and hard-working What You Care About: Learning from leaders who are dedicated to your success Working in a role you genuinely love with people you enjoy being around Making an impact in the fast-paced world of data Growing your leadership skills for a long and rewarding career You’ll Contribute By: Maintaining, creating, and updating accurate customer, pipeline, and forecast information in Salesforce Using knowledge of the data and analytics space to interact with a diverse set of businesses in consultative sales Owning your sales process — from first call to demo to proposal to proof of concept to contract Working alongside a team of motivated reps on a high-functioning, energetic team Bringing on new customers and developing advocates for Sigma in the business intelligence market Engaging with partners in the data ecosystem to build pipeline or support specific customer needs and initiatives Generating new revenue for a rapidly growing company Your Qualifications: Ideally two or more years of experience closing deals Experience in the data analytics or BI space (Looker, Tableau, Domo, etc.) is preferred Background in high-tech software sales is

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

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 is used by more than half of the Fortune 500 companies to power their mission-critical initiatives. Enterprise customers leverage Airtable to build sophisticated apps, and orchestrate deep, end-to-end workflows. As we continue to scale, our teams are building the systems to ensure the security and governance of our customer’s data - from secure handling of file attachments to enterprise key management. These are advanced systems that provide robust security measures to protect our user’s data. We are seeking Engineering Managers to join our Enterprise engineering pillar, focused on scaling product experiences for our biggest customers. We currently have openings on: The Admin & Governance Team: As AI becomes central to Airtable, enterprise customers need governance controls that let them adopt AI confidently, with granular feature enablement, capability-based restrictions, and full admin visibility. The Admin & Governance team is building that control plane – the AI Governance framework that gives admins those controls at every level of the enterprise. This work builds on the team's deep ownership of Airtable's enterprise trust infrastructure: the Admin Panel, SSO, audit systems, and User Groups that power governance for our largest customers. We're looking for a leader who can drive the AI Governance roadmap, scale the team's existing enterprise trust systems, and directly unblock adoption for our largest customers. Please note: while we employ a hybrid working model at Airtable (flexible in working from the office or elsewhere), we are looking to hire candidates at this level that are based in San Francisco or New York City who are open to coming into the office at least ~2-3 times/week for

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

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

Summary We are looking for a detail-oriented and dedicated Administrative Assistant to provide support to our Portfolio Managers and Analysts within our Point72 office in San Francisco, CA. What you’ll do The Administrative Assistant will provide administrative support to one or several investment teams including Portfolio Managers and Research Analysts. Specifically, you will: Strategically partner with investment team(s) to help alleviate workload and create efficiencies Manage calendars and conference calls, make appointments, book conference rooms, organize meetings Coordinate domestic and international travel arrangements Create and process expense reports Manage phone coverage for team and set up conference calls as needed Develop and maintain strong working relationships with internal and external partners Work on special projects as needed What’s required 2+ years of relevant work experience Bachelor’s degree from an accredited university Capacity to multitask, effectively prioritize and adapt to an ever-changing work environment Bring a “roll up your sleeves and get the work done” mentality and a sense of urgency and attention to detail to requests and projects Excellent communication and ability to interact with people of all levels in a confident and professional manner Strong attention to detail; can keep track of multiple projects and work through abstract issues in an organized and efficient manner Proficient knowledge of Microsoft Outlook, Excel, and Word Strong industry knowledge preferred Commitment to the highest ethical standards We take care of our people We invest in our people, their careers, their health, and their well-being. When you work here, we provide: Fully-paid health care benefits Generous parental and family leave policies Volunteer Opportunities Support for employee-led affinity groups representing women, people of color and the LGBTQ+ community Mental and physical wellness programs Tuition assistance A 401(k) savings program with a

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

Scale Labs, Research Scientist — AI Controls and Monitoring 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 focused on AI Controls and Monitoring, you will design methods, systems, and experiments to ensure that advanced AI models and agents remain aligned with intended goals, even in high-stakes or adversarial environments. For example, you might: Develop monitoring techniques and observability methods that track AI behavior in real time to identify and flag deviations, emergent capabilities, or anomalous outputs; Research mechanisms for layered control, including fail-safes, oversight protocols, and intervention methods that can halt or redirect AI systems when risks are detected; Design red-team simulations to probe weaknesses in oversight and control mechanisms, and build mitigations to close identified gaps; Collaborate with policymakers, engineers, and other researchers to establish standards and benchmarks for AI monitoring and escalation. 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

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 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

Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including frontier model training, enterprise adoption, defense applications, and autonomous vehicles. Our mission is to develop reliable AI systems for the world's most important decisions. The next frontier for AI is the physical world. We're looking for an AI Product Manager to own the Robotics vertical within our Physical AI team. In this role, you'll own both the development of the data and training environments (the teleoperated demonstrations, real-world collections, simulated tasks, and annotation products that labs use to train and evaluate robot policies) and the "data as a product" strategy that powers them. You'll understand where physical AI is headed, decide what robot tasks and embodiments are worth collecting, how to source and structure the underlying data, and how to turn deep domain knowledge into a defensible product. The ideal candidate has lived inside robotics or physical AI research, and is able to pair that domain understanding with a sense for where current robot policies succeed and fail in real-world workflows. You'll translate that expertise into datasets, environments, and evaluation frameworks that teach robots to do real physical work, and you'll be the domain expert Scale's most important customers and their leading researchers turn to. A strong entrepreneurial & go-to-market mindset will be necessary. What You'll Do Own the Robotics AI roadmap & data strategy: Set product direction for the robotics training stack and the data strategy behind it — what data we collect, on which hardware and embodiments, and what we source internally vs. through our marketplace. Establish a vision for where physical AI is heading, driving execution across engineering, operations, and go-to-market teams. Build partnerships with research teams at frontier labs: Work directly with researchers at leading physical AI labs to understand where their robot p

About Scale AI Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with leading enterprises and government organizations to accelerate their AI initiatives through our data annotation platform, generative AI solutions, and enterprise AI capabilities. Role Overview As a Senior Staff Frontier Agents Engineer on our Enterprise team, you'll be the technical bridge between Scale AI's cutting-edge AI capabilities and our most strategic customers. You'll work with enterprise clients to understand their unique challenges, architect custom AI solutions, and ensure successful deployment and adoption of AI systems in production environments. This is a hands-on technical role that combines deep engineering expertise with customer-facing problem solving. You'll work directly with customer engineering teams to integrate AI into their critical workflows. Key Responsibilities Customer Integration & Deployment Partner directly with enterprise customers to understand their technical infrastructure, data pipelines, and business requirements Design and implement custom integrations between Scale AI's platform and customer data environments (cloud platforms, data warehouses, internal APIs) Build robust data connectors and ETL pipelines to ingest, process, and prepare customer data for AI workflows Deploy and configure AI models and agents within customer security and compliance boundaries AI Agent Development Develop production-grade AI agents tailored to customer use cases across domains like customer support, data analysis, content generation, and workflow automation Architect multi-agent systems that orchestrate between different models, tools, and data sources Implement evaluation frameworks to measure agent performance and iterate toward business objectives Design human-in-the-loop workflows and feedback mechanisms for continuous agent improvement Prompt Engineering & Optimization Create sophisticate

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 the ACE team The Agent Capabilities & Environments (ACE) team, part of Scale’s Research organization, brings together customer-facing Researchers and Applied AI Engineers. Our core mission includes research on agent environments and RL reward signals, benchmarking autonomous agent performance across real-world scenarios and environments, creating robust data programs to improve Large Language Models (LLMs) agentic capabilities and building foundational tools and frameworks for evaluating models as agents. ACE focuses on autonomous agents that dynamically interact with diverse external environments, including code repositories, GUI interfaces, browsers, and more. About This Role This role is at the intersection of cutting-edge AI research and practical application, with a focus on studying the data types essential for building state-of-the-art agents, such as browser and SWE agents. The ideal candidate will explore the data landscape needed to advance intelligent, adaptable AI agents, guiding the data strategy at Scale to drive innovation. This position requires not only expertise in LLM agents and planning algorithms but also creativity in addressing novel challenges related to data, interaction, and evaluation. You will contribute to impactful research publications on agents, collaborate with customer researchers, and work alongside the engineering team to translate t

Scale Labs, Research Scientist — Safety Post Training 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 Safety Post-Training you will develop and apply post-training methods and interpretability techniques to make frontier AI systems safer, and better understood by researchers and policymakers.. For example, you might: Design and run post-training pipelines to study how training choices affect model safety, robustness, and alignment properties; Develop interpretability-informed evaluations that reveal how and why models produce unsafe, deceptive, or otherwise undesirable behaviors, and use those insights to guide targeted mitigations; Collaborate with policymakers, engineers, and other researchers to translate post-training and interpretability findings into actionable safety standards, evaluation benchmarks, and best practices. 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. Experience with post-training and RL techniques such as RLHF, DPO, GRPO, and similar approaches. A track record of published research in machine learning, particularly in generati