Ai Research Scientist in San Francisco

National Security Hackathon Attendees – Stay Connected with Scale AI This posting is for candidates who attended National Security Hackathon and connected with a member of the Scale AI team. It was great meeting you at the Hackathon! Whether we spoke at our booth or on the floor, we always enjoy connecting with people who are passionate about advancing AI and machine learning. At Scale AI, our mission is to develop reliable AI systems for the world's most important decisions. For the past ten years, Scale has been the leading AI data foundry, supporting some of the most exciting advancements in AI, including generative AI, defense applications, robotics, and autonomous systems. We’re continuing to grow our team across a range of technical and mission-focused roles. If you're excited about the problems we’re tackling, feel free to share your information here. A member of our team will reach out if there’s a strong fit with one of our open opportunities. And even if the timing isn’t right today, we’d love to stay connected. We look forward to continuing the conversation. In the meantime, you can learn more about our work at scale.com . Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: c

Scale GP (Scale Generative AI Platform) is an enterprise-grade AI platform that provides APIs for knowledge retrieval, inference, evaluation, and more. We are looking for a strong engineer to join our team and help us build and scale our core infrastructure in a fast-paced environment. The ideal candidate will have a strong understanding of software engineering principles and practices, as well as experience with large-scale distributed systems. You will implement solutions across multiple cloud providers (GCP, Azure, AWS) for customers in diverse, highly-regulated industries like healthcare, telecom, finance, and retail. What You’ll Do: Architect multi-cloud systems and abstractions to allow the SGP platform to run on top of existing Cloud providers Implement custom integrations between Scale AI's platform and customer data environments (cloud platforms, data warehouses, internal APIs) Collaborate with platform, product teams and our customers directly to develop and implement innovative infrastructure that scales to meet evolving needs. Deliver experiments at a high velocity and level of quality to engage our customers Work across the entire product lifecycle from conceptualization through production Be able, and willing, to multi-task and learn new technologies quickly What We’re Looking For: 4+ years of full-time engineering experience, post-graduation Experience scaling products at hyper growth startups Experience tinkering with or productizing LLMs, vector databases, and the other latest AI technologies Proficient in Python or Javascript/Typescript, and SQL Experience with Kubernetes Experience with major cloud providers (AWS, Azure, GCP) Excellent communication skills with the ability to explain technical concepts to both technical and non-technical audiences Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries fo

Scale's mission is to develop reliable AI systems for the world's most important decisions. We provide the high-quality data that powers the world's AI models, and we help enterprises and governments build, deploy, and oversee AI applications that create real impact. As Communications Manager, Corporate and Product, you will help shape how Scale shows up when it comes to our work building enterprise AI, spanning company narrative, product launches, partner communications, media presence, and executive visibility. This role is centered on translating complex enterprise AI deployments and partnerships into clear, compelling narratives that resonate with business and vertical industry audiences. A core focus of the role is pitching and positioning Scale's enterprise wins, product launches, and customer partnerships, including how organizations across industries are using Scale's Generative AI Platform to build, deploy, and oversee AI applications that create real impact. You will also work closely with communications counterparts at partner companies to align messaging and coordinate joint announcements. You will help tell the story of how Scale's enterprise business powers mission-critical AI programs for the world's most consequential organizations, from Fortune 500 companies to leaders across every major industry. In this role, you will partner closely with enterprise product leaders and go-to-market teams, as well as teams across communications, social, and marketing. You will play a key role in strengthening Scale's reputation with enterprise customers, industry analysts, and the broader technology ecosystem. This position reports directly to the Head of Corporate & Product Communications. You Will Support corporate and product communications initiatives with a strong emphasis on Scale's enterprise business, including customer and partnership announcements, product launches, executive visibility, and industry positioning. Help translate co

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 Forward Deployed AI Engineering Manager 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, lead a team that architects specific AI solutions, and ensure successful deployment and adoption of AI systems in production environments. This is a Management role that combines deep engineering and AI expertise, leading a team, and working on customer-facing problems. 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 Engineeri

At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. Scale Frontier Data is the organization behind the training and evaluation data that frontier labs depend on. We build the systems, tooling, and expert workflows that turn hard human expertise into signals that models can learn from, across reasoning, coding, agentic tool use, and domain expertise. About our Customer Platform team: Our Customer Platform Team plays a pivotal role in integrating our platform with external systems and ensuring seamless, reliable connectivity for both internal users and customers. As the leader of this team, you’ll drive the strategy, architecture, and development of our connectivity solutions, focusing on API integration, distributed systems, and a robust data platform. Your role will be crucial in maintaining and enhancing our platform’s ability to meet the needs of both our internal and external stakeholders. Responsibilities: Own large areas within our product Comfortable working cross functionally, whether that be internal or external customers Build features end-to-end: front-end, back-end, system design, debugging and testing Deliver experiments at a high velocity and level of quality to engage our customers Work across the entire product lifecycle from conceptualization through production Influence the culture, values, and processes of a growing engineering team Inspire and mentor less experienced engineers Collaborating with cross-functional teams to define, design, and ship new product features and experiences. Requirements: At least 7-10 years of relevant experience is preferred Track record of shipping high-quality products and features at scale Desire to work in a very fast-paced environment Abil

Overview Scale’s Finance Systems and Automation team is looking for a builder-oriented team member to help design and develop integrations, automations, and AI agents that streamline workflows across Finance, Accounting, People, and Recruiting. In this role, you will work closely with stakeholders across Finance, Accounting, People Operations, and Recruiting to understand their workflows and build integrations, automations, and agentic workflows that reduce manual effort and accelerate execution across these teams. You will leverage our internal data infrastructure, system integration tooling, and emerging AI platforms to architect scalable solutions — from traditional system integrations to intelligent agent-driven workflows — that serve as the foundation for long-term operational efficiency. We’re looking for someone who thrives on connecting systems, automating repetitive processes, and pushing toward more autonomous, AI-assisted operations. You should be comfortable navigating ambiguity, designing solutions that scale, and rigorously validating outcomes end to end. What You’ll Do Design and build agent-driven workflows and automation systems across People Operations, Recruiting, Finance, and Accounting Identify opportunities to replace manual or rules-based processes with agentic workflows Partner with stakeholders to translate business processes into scalable, automated solutions Lead the implementation of end-to-end workflows, from requirements through deployment and validation Automate candidate-to-employee transitions (e.g., Greenhouse → HRIS → provisioning systems) Build workflows to manage employee lifecycle events such as onboarding, transfers, and offboarding Automate approval flows and data synchronization across People, Finance, and Recruiting systems Support accounting and finance workflows through scalable integrations and automation Design and implement the underlying integrations and data flows that enable reliable automation and agent behavior Est

Head of Enterprise GTM Strategy & Operations Reports to VP, Enterprise Sales · SF or NY Reporting to the VP of Enterprise Sales, this role owns both halves of Scale AI’s enterprise revenue engine: the strategy that determines where we play and how we win, and the operating system - people, process, and systems - that makes that strategy executable, measurable, and repeatable. On the strategy side, you set the analytical foundation for enterprise growth: segment and account prioritization, coverage and territory design, pricing and packaging inputs, and the diagnostic work that explains why the funnel behaves the way it does. On the operations side, you own the RevOps stack, forecasting, compensation design, sales enablement, and the operating cadences that convert strategy into predictable quarterly execution. The ideal candidate is equally comfortable building a segmentation model from a blank page and running a Monday morning pipeline review. You will lead an established team, with the Head of Sales Enablement and the RevOps Manager as direct reports. Your first job is to raise the ceiling on what that team delivers: sharper analysis, tighter operating rhythm, and enablement that measurably shortens ramp and lifts win rates. This is a senior, highly visible role partnering with Enterprise Sales leadership, Finance, Marketing, Product, and Solutions Engineering, with regular exposure to the executive team and board materials. STRATEGY Define which segments, industries, and accounts Scale prioritizes, and build the analytical case behind those choices Build and maintain the market sizing, segmentation, and account-tiering models that drive coverage decisions and investment trade-offs Lead hypothesis-driven analyses of the enterprise funnel - win/loss patterns, conversion drivers, deal economics, coverage gaps - and translate findings into specific changes to how we sell Partner with Finance and Product on pricing, packaging, and deal-structure strateg

You will: Source and acquire quality candidates for high volume positions to meet hiring and activation goals Review applications and screen candidates Support candidates throughout the recruiting process Partner with other growth recruiters, ops leads and cross-functional leaders to understand Scale’s business needs, then devise and execute on the recruiting strategy needed to deliver on them. Follow and manage processes that will evolve over time as the company grows. Represent and champion the brand, promoting its value proposition to candidates and driving engagement. Represent Scale at occasional onsite growth recruiting events. Ideally you have: 2+ years of recruiting/sourcing experience in a fast-paced, high-growth environment. Excellent written and verbal communication skills, with the ability to tailor messaging to diverse audiences Experience sourcing candidates and filling high volume roles Experience acting as the primary candidate liaison, delivering white-glove service through timely updates and personalized support throughout the interview process Nice to have: Previous experience in a start-up. Either experience managing a full-cycle recruiting experience, or a passion and ability to learn to do so. Experience with various tools such as Linkedin Recruiter, Clay, Modernloop, Gem Extreme attention to detail AI builder, AI-forward operator, or strong interest in agentic coding and experimenting with AI tooling The hourly salary range for this position is $40 to $55/hr. This is a remote position with occasional travels required for onsite growth recruiting events. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allow

Owns day-to-day deal pricing execution for Enterprise, including pricing calculations, staffing inputs, and dashboard reporting that gives Sales and Deal Desk leadership visibility into deal status, pricing, and margin. Partners with the Deal Desk Manager on customer deal structuring and on identifying ways to accelerate the deal approval process. What You’ll Do Deal Pricing Execution Manages day-to-day deal pricing calculations for Enterprise deals, including ROI modeling and EPD staffing inputs Applies existing pricing frameworks consistently across Land, Expansion, and Framework deals Partners with the Deal Desk Manager to design customer-specific deal structures for non-standard or complex deals Pricing & Deal Status Reporting Builds and maintains a pricing dashboard tracking deal status, pricing, margin, and overall deal health across the Enterprise pipeline Updates pricing and trend reporting to keep leadership current on where deals stand and how pricing is trending against targets Process Optimization Identifies bottlenecks in the deal review & approval process and proposes ways to accelerate cycle time Helps standardize and streamline recurring pricing/approval steps into repeatable, lower-friction workflows Tracks deal approval cycle time and surfaces trends to inform process improvements Cross-Functional Deal Coordination Owns deal crafting end-to-end from initial pricing/modeling through contract review, coordinating with sales management, reps, and internal stakeholders Ensures the relevant stakeholders (Accounting, Finance, EPD, Legal) review and approve deals at the appropriate stage before they progress Routes deal packages to the correct reviewers and tracks open items so deals aren't stalled waiting on sign-off Strategic & GTM Support Tackles ambiguous, open-ended questions around Scale's go-to-market motion and iterates quickly on solutions that deliver measurable results Supports Sales and Finance leadership in quarterly strategy and

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 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

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 Senior Software Engineer, you will lead 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: Lead the design and implementation of scalable backend systems and distributed architectures for Federal customers. Manage the full lifecycle of feature development from requirement definition to deployment on classified networks. Direct the orchestration of asynchronous agent fleets to meet mission requirements. Lead customer engagements to translate mission needs into technical requirements. Own the communication with stakeholders to ensure implementation meets defined acceptance criteria. Conduct technical reviews and identify risks within machine learning infrastructure and model serving. Drive the platform roadmap by providing technical specifications for Federal product offerings. 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 contai

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

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

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