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, and quickly turning new ideas from the research literature into working prototypes.
• 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 generative AI.
• At least three years of experience addressing sophisticated ML problems, whether in a research setting or in product development.
• Strong written and verbal communication skills to operate in a cross-functional team.

Nice to have:

• Hands-on experience with agent evaluation frameworks such as SWE-bench, WebArena, OSWorld, Inspect, or similar tools.
• Experience with red-teaming, prompt injection, or adversarial testing of AI systems.

Our research interviews are crafted to assess candidates' skills in practical ML prototyping and debugging, their grasp of research concepts, and their alignment with our organizational culture. We will not ask any LeetCode-style questions. If you’re excited about advancing AI safety and contributing to our mission, we encourage you to apply, even if your experience doesn’t perfectly align with every requirement.

We are building out the Finance team to help make data-driven and financially sound decisions for Scale. The Finance team drives strategic, financial, and operational decisions by partnering with the leadership team to make critical decisions across Scale.

We’re looking for a high-performing, all-rounded finance athlete to join our team and support the rapidly growing Generative AI (GenAI) business. You’ll collaborate closely with Product, Operations, Growth, and Go-to-Market leaders to bring financial rigor to decision-making, develop actionable insights that drive strategy, and build scalable systems as the business expands.

This role is ideal for someone with 4-6 years of experience in a fast-paced, high-growth environment. Someone who thrives in ambiguity, can juggle multiple workstreams, and brings a mix of analytical rigor, business acumen, and strong execution.

You will:

• Own and evolve part of the GenAI financial forecasting model, driving accuracy and insight across planning cycles
• Support reporting and performance management, including weekly and monthly reviews, consolidations, and ad hoc analyses
• Partner with GenAI leadership and cross functional teams to evaluate and execute key strategic and operational initiatives that scale the business multifold
• Conduct financial analyses and build business cases for new products, partnerships, and investments
• Collaborate with Accounting, and Corporate Finance to improve close, reporting, and planning cadences
• Continuously improve financial processes and systems to enhance scalability, forecast precision, and data visibility

Ideally, you'd have:

• 4–6 years of experience in Strategic Finance, FP&A, or Business Operations, ideally within a high-growth technology company
• 2 years of investment banking experience at a top-tier firm 
• Strong analytical and financial modeling skills; ability to translate complex data into actionable insights
• Excellent communication skills, with the ability to distill complexity into clear narratives for non-finance stakeholders
• Advanced proficiency in Excel, Google Sheets, and PowerPoint; strong command of financial modeling best practices
• Experience with SQL or Business Intelligence tools (e.g., Looker, Tableau)
• Familiarity with Anaplan, Adaptive Insights, or other planning systems

Nice to haves:

• Bachelor’s degree in Finance, Accounting, Economics, Engineering, or a related field
• Prior experience supporting Product, Engineering, Growth, or Operations teams within a technology company

Scale exists to accelerate the development of AI applications. We believe that creating and harnessing the power of AI is both wildly ambitious and the most impactful opportunity we can be working on. To that end, we are looking for a very specific candidate for the Business Operations & Strategy team - a hard charging generalist that is obsessed with impact, deeply analytical, low ego, and ready to embrace the intensity required to achieve our goals. If you are an experienced operator who excels at solving hard problems while building strong teams and relationships, we want to hear from you!

The team

The Business Operations & Strategy team is a tight-knit group that drives mission-critical initiatives across the breadth of Scale, supporting product, engineering, sales, marketing, and core operations by providing planning, analytical, operational, and strategic support. 

As Scale continues to rapidly grow, most of the problems we face have ambiguous causes and unknown solutions - we cannot pattern match our way to winning. The BizOps team dives deeply into Scale’s biggest challenges on a project-basis, driving clarity and outcomes by breaking down the problem in a highly structured way. This means that every member of the BizOps team must be highly operational, ready to shift between strategic, cross-functional projects and rolling up our sleeves to run day-to-day operations; no job or task is too small.

You will:

• Take on Scale’s difficult-but-ambiguous problems, breaking them down in a structured way and driving them to successful outcomes
• Dive deeply into our operations and data - you will become an expert on how Scale operates, and develop a deep understanding of the AI industry
• Build high trust relationships across the organization to partner with and influence outcomes beyond what you directly touch
• Have full ownership of your work and outcome - we support each other as a team, but you will have broad latitude to run autonomously as you get up to speed 
• Partner with, influence, and support the Scale executive team as we tackle the most difficult decisions in the business
• Help incubate, seed, and scale new teams
• Design, manage, and iterate on the operational and analytical systems and processes that make Scale hum
• Eventually spin out to take on full ownership of a given role, team, or opportunity in Scale

Ideally you would have:

• The ability to run on your own, operating at the highest level in a rapidly changing industry during a period of hypergrowth
• A penchant for digging deeply into the data yourself, thinking from first principles, and iterating quickly to deliver results
• A strong orientation toward outcomes, and a history of being scrappy when it counts
• Low ego - you will be joining a team of truly exceptional generalist athletes, there is no room for ego
• An easygoing interpersonal style that you bring to bear in everything from deep technical conversations with engineers to polished executive level comms
• Proven ability to build high trust relationships with a wide range of people across the organization
• A history of developing lightweight processes and getting them adopted
• Experience in product or project management, taking projects from conception to launch
• Excellent qualitative and quantitative analytical skills

Nice to haves:

• 4+ years of experience in a highly strategic, analytical and operational role within a rapidly growing company
• 2+ years consulting (McKinsey, Bain, or BCG preferred), investment banking, private equity, or hedge fund experience
• Top MBA
• Experience with SQL or a willingness/aptitude to learn

Scale AI is seeking a highly motivated Senior Accountant to join our growing accounting team and assist in preparing day to day corporate accounting operations, supporting the month end close process, and helping to implement systems and processes that will support Scale as we continue to grow. You’ll have the opportunity to work in a dynamic, fast and high-growth environment.

The ideal candidate thrives in a high-growth start-up, is detail-oriented, and has excellent interpersonal and communication skills. Additionally, the candidate has demonstrated the ability to build scalable cross-functional relationships through systems and process implementation. We hope you will join our team!

You Will:

• Prepare journal entries and day to day corporate accounting activities, support the month end close process, and provide timely and accurate month-end close financials that are U.S. GAAP compliant 
• Build or enhance balance sheet account reconciliation workpaper including reviewing and performing some clean-up of historical reconciliations and related balances
• Collaborate within Accounting and Finance teams on metrics, flux analysis, forecast, and projections and support preparation of the monthly reporting package
• Prepare documents supporting internal and external audits and ensure the successful completion of those audits
• Support the implementation of new systems, tools, and processes to streamline close and build scalable solutions to support the growth of the Company
• Identify and drive process improvements to gain efficiencies and reduce close timeline
• Develop, maintain and improve internal controls which relate to assigned areas

Ideally You Have:

• Bachelor’s degree in Accounting; CPA or in the process of working towards one.
• 3+ years of relevant accounting experience; Combination of public accounting (Big 4 strongly preferred) and industry experience (start-up through to becoming a public Company experience a plus)
• Strong knowledge of U.S. GAAP and SOX
• Experience with general ledger functions and the month end/year end close process is strongly preferred
• Experience with financial audit preparation is strongly preferred
• Proven proficiency of Microsoft Office Suite (Word, PowerPoint, etc); must be highly proficient in Excel
• Excellent writing, oral communication, analytical, organizational, and interpersonal skills with a high attention to detail
• Excellent problem solving skills; project management experience a plus, ability to work in a fast pace environment

Nice to Haves: 

• Direct accounting experience for any/all of the following areas: accruals, investment, internally use software, ASC 842 leases, cloud computing arrangement, stock-based compensation and/or consolidation and Fx.
• Proficiency in SQL, NetSuite, FloQast, Coupa and Jira considered a plus

Scale AI operates a global two-sided marketplace. On the demand side, AI labs and enterprises need high-quality training data. On the supply side, 500,000+ contributors across 100+ countries perform the annotation, evaluation, and data-generation work that makes frontier AI possible. For example, our contributor network includes Math PHDs from Vietnam, law professors at top colleges and investment bankers modeling efficient capital structures - all in service of training next-gen AIs. Keeping this marketplace trustworthy and free from fraud is foundational — to contributor experience, to customer data quality, and to the health of the business.

We are looking for a senior Product Manager to lead Trust & Safety at Scale. This is a high-autonomy, high-impact role. You will own the product strategy for fraud detection, prevention, and remediation across our contributor ecosystem — building the systems that protect our platform from abuse while preserving a fair, transparent experience for legitimate contributors. T&S at Scale intersects every part of the contributor lifecycle: onboarding, task assignment, quality assessment, and payments. The scope is global, the adversaries are sophisticated, and the stakes are real.

This role requires deep domain expertise in fraud and trust & safety. You should bring a strong point of view on how to build world-class T&S systems — because you will be the resident expert. You will set the vision for moving T&S from a reactive, fire-fighting posture to a proactive, intelligence-driven function with scalable detection and prevention infrastructure.

About the Role:

• You will be the most senior T&S product leader at Scale, reporting directly to the Head of GenAI Product. You will have dedicated engineering, data science, and operations partners, and will work closely with EPD leadership and Delivery Ops.
• T&S at Scale is not a mature function — it has been built reactively over time in response to specific fraud incidents. The platform needs a cohesive strategy that balances fraud mitigation with contributor growth, reduces false positives, and replaces ad-hoc solutions with scalable systems. You will inherit a patchwork of existing tools, signals and products and shape them into a coherent, defensible platform with mature processes.
• The contributor marketplace creates unique fraud vectors: account farming, task manipulation, quality gaming, payment fraud, and collusion — all evolving as AI capabilities change. You need to stay at the leading edge of adversarial behavior in AI-native marketplaces.
• This is a highly cross-functional role. You will collaborate with stakeholders across Ops, EPD, Finance, and leadership. Fires happen weekly. You need to be the person who navigates complexity and drives resolution efficiently.

You will:

• Set the product vision and strategy for Trust & Safety at Scale, shifting the function from reactive incident response to proactive, intelligence-driven fraud prevention
• Own the product roadmap for fraud detection, prevention, and remediation systems — including the Risk Engine, data signals intelligence, anomaly detection, and contributor investigation tooling
• Build a balanced approach to fraud mitigation and growth protection — ensuring T&S interventions don’t unnecessarily throttle the contributor funnel or create friction for legitimate users
• Investigate and deeply understand contributor behavior patterns to identify emerging fraud vectors before they become material
• Drive cross-functional alignment across Ops, EPD, Finance, and executive leadership — independently handling escalations, stakeholder conflicts, and weekly fire drills without requiring constant HM involvement
• Translate complex fraud patterns into clear product requirements for engineering, and partner with data science to build and improve detection models
• Build long-term instrumentation, monitoring, and evaluation capabilities to measure fraud rates, false positive rates, contributor impact, and financial exposure
• Establish business cases quantifying fraud losses and ROI of prevention investments to secure resources and prioritize effectively
• Partner with Finance and Delivery Ops leadership to manage the financial impact of fraud on business profitability

Ideally, you’d have:

• 8–12 years of experience in Product Management in the tech industry, with at least 3–4 years leading Trust & Safety, Fraud, or Risk product teams
• Deep domain expertise in fraud (not security) — specifically consumer product fraud, marketplace fraud, or contributor/gig-economy fraud. FinTech/payments fraud alone is not sufficient; we need someone who understands platform-level abuse and adversarial user behavior
• Track record of building T&S systems at consumer-facing marketplace companies (e.g., Uber, DoorDash, Airbnb, eBay, Instacart) or similar high-growth platforms with global contributor/user bases
• Proven ability to balance fraud mitigation with growth protection — you’ve made hard tradeoff decisions between blocking bad actors and preserving good UX
• Exceptional stakeholder management skills — you’ve navigated complex orgs with Ops, Engineering, and leadership stakeholders who have competing priorities and strong opinions. You handle escalations, build trust, and drive alignment independently
• Strong analytical capabilities — you can investigate contributor behavior data, define fraud metrics, and build detection logic. High proficiency in SQL
• Experience setting ambitious product vision and executing against it — you’ve moved a function from reactive to proactive
• Bachelor’s or advanced degree in a quantitative, engineering, or related discipline

Nice to Have:

• Experience building T&S systems with global/international coverage across diverse contributor populations
• Understanding of AI-enabled fraud vectors and how adversarial behavior evolves as AI capabilities improve
• Experience with contributor/gig-economy platforms specifically (not just consumer marketplaces)
• Experience working at early-to-growth-stage companies where T&S was being built or rebuilt from scratch

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.

About the General Agents Team

The General Agents team, part of Scale’s Enterprise organization, builds robust general agents for customer use cases and applications. The team sits at the intersection of frontier agent development and real-world deployment, translating state-of-the-art reasoning and agentic capabilities into reliable, production-grade systems that drive real economic value. Our agents are scalable systems built around recurring enterprise problem domains, with a strong emphasis on generalization, extensibility, and deployment across many customers.

About the Role

As a Senior/Staff Machine Learning Engineer (MLE) on the General Agents team, you’ll play a critical role in designing, building, and deploying production-ready AI agents that solve high-impact enterprise problems. You will work across the full agent lifecycle—from model and system design to evaluation, deployment, and iteration—bridging cutting-edge agentic techniques with the constraints and requirements of real customer environments.

You will:

• Design and implement end-to-end agent systems that combine LLM reasoning, tool use, memory, and control logic to solve recurring enterprise use cases.
• Build scalable, reliable agent architectures that can be deployed across many customers with varying data, tools, and constraints.
• Develop evaluation frameworks, datasets, environments, and metrics to measure agent performance, reliability, and business impact in production settings.
• Collaborate closely with product managers, customers, data annotators, and other engineering teams to translate enterprise requirements into robust agent designs.
• Productionize frontier agent techniques (e.g., planning, multi-step reasoning and tool-use, multi-agent patterns) into maintainable, observable systems.
• Own deployment, monitoring, and iteration of agent systems, including failure analysis and continuous improvement based on real-world usage.
• Contribute to technical direction and architectural decisions for general agent development best practices and methods, with increasing scope and leadership at the Staff level.

Ideally you’d have:

• 5+ years of experience building and deploying machine learning or AI systems for real-world, production use cases.
• Strong engineering fundamentals, supported by a Bachelor’s and/or Master’s degree in Computer Science, Machine Learning, AI, or equivalent practical experience.
• Deep understanding of modern LLMs, prompt-, context-, and system-level optimization, and agentic system design.
• Proven proficiency in Python, including writing production-quality, testable, and maintainable code.
• Experience building systems that integrate models with external tools, APIs, databases, and services.
• Ability to operate in ambiguous problem spaces, balancing research-driven approaches with pragmatic product constraints.
• Strong communication skills and comfort working in customer-facing or cross-functional environments.

Nice-to-haves:

• Hands-on experience building AI agents using modern generative AI stacks (OpenAI APIs, commercial or open-source LLMs).
• Experience with agent frameworks, orchestration layers, or workflow systems (e.g., tool calling, planners, multi-agent setups).
• Familiarity with evaluation, monitoring, and observability for LLM-powered systems in production.
• Experience deploying ML systems in cloud environments and operating them at scale.
• Experience fine-tuning or adapting foundation models using methods like supervised fine-tuning (SFT), reinforcement learning with verifiable rewards (RLVR), and low-rank adaptation (LoRA) to improve agent performance on domain-specific tasks.
• Interest in shaping the future of general-purpose enterprise agents and their real-world impact.

The next frontier for AI is the physical world. At Scale, we're pioneering this shift, moving artificial intelligence from digital spaces into robotics and autonomous systems. Our Robotics team is building the data platform that will power the future of Physical AI. We are looking for a pivotal Solutions Engineer, to be based in our San Francisco Corporate Headquarters.

As a Solutions Engineer, you'll be a trusted technical partner, building deep relationships with some of the world's most innovative model builders and renowned robotics companies.  You will partner closely with Product, Sales and Machine Learning Engineers to guide prospective customers through the pre-sales process, delivering customized demos and pilots that secure the "technical win." You'll define customer technical requirements, develop actionable Statements of Work, and collaborate with the delivery team on initial implementation. Your relentless curiosity about customer needs, combined with your expert knowledge of Scale's products will allow you to design creative and impactful solutions.

This is a critical role that directly influences multi-million dollar contracts and initiatives. You'll travel globally to conduct on-site technical workshops and scope new projects, while also leading demos and pilots for new prospects. You'll be part of a tight-knit, specialized team, influencing a rapidly growing business that is expanding into new product areas.

In this role, you will:

• Partner with Scale Account Executives and Engagement Managers to deliver new customer pilots and grow technical relationships with existing clients.
• Work with Product Engineering and Product Management to influence our product roadmap based on your frontline insights.
• Become a domain expert in next-generation Robotics and physical AI (e.g. VLMs, VLAs, World Models)
• Be accountable for the technical customer experience and commercial growth, expanding relationships and use cases with existing customers.
• Collaborate with highly technical engineers at our customer sites to ensure satisfaction with our data, software platforms, and workflows.
• Design and develop playbooks, demos, and other tools to ensure efficient and successful pilots and customer expansions.
• Pioneer the development of a global Robotics Data Marketplace, actively seeking out and engaging with key international partners to build a comprehensive data ecosystem.
• Evangelize Scale by interacting with customers at major industry events and academic conferences.

You have:

• A strong engineering background, preferably in Robotics, Mechatronics, Computer Science, Mathematics, or other Engineering fields.
• 3+ years of experience developing with Python, C++, Java, and/or other scripting languages.
• Hands-on experience in Robotics and Physical AI
• Exceptional project management and interpersonal skills, strong attention to detail, and a strong sense of ownership.
• The presentation skills and technical credibility to speak confidently with a variety of stakeholders, from executives to front-line engineers.
• A high level of comfort communicating effectively across internal and external organizations.
• Regular travel within the Bay Area.
• International travel approximately once every two months.
• Intellectual curiosity, empathy, and the ability to operate with a high degree of autonomy.

Bonus points if you have:

• Prior sales, solutions engineering,  or partnership experience with a track record of successfully achieving quota.
• Ideally would have experience selling complex technical solutions to enterprises with deal sizes of $500K to $5M+.

About the Role Scale is at the frontier of GenAI and human-AI collaboration. The Gen AI Ops Trust and Safety team is focused on safeguarding human authenticity and genuineness in AI training. We are looking for a highly analytical Technical Program Manager (TPM) who leans heavily into fraud analytics and data-driven strategy to protect our ecosystem.

This isn't a project management role. You will act as the lead investigative analyst and program owner for our fraud defense portfolio. Your day-to-day will involve diving deep into complex datasets to uncover hidden fraud vectors, and then translating those analytical insights into scalable rules, policies, and operational programs. By utilizing AI coding tools at high velocity, you will build out analytics pipelines, dashboards, and detection logic to shift Trust and Safety from a reactive function to a strategic one that balances safety and growth.

You will:

• Analyze large, messy behavioral events to identify ambiguous and constantly evolving fraud patterns across the contributor lifecycle.
• Translate your analytical findings into actionable detection logic. You will redesign rules, optimize thresholds, and decision flows to catch bad actors while minimizing friction for high-quality contributors.
• Establish robust KPIs, build tracking dashboards, and define offline evaluation frameworks (e.g., false positive monitoring, precision/recall analysis) to continuously measure the health of our risk strategy.
• Act as the connective tissue between data, operations, and engineering. You will use your analytical findings to implement technical execution, taking new detection capabilities from data prototype to production deployment.
• Leverage AI-assisted IDEs daily to rapidly write complex SQL queries, automate data pulls, and streamline your analytical workflows.
• Connect signals, data, and operations to see the full picture. Provide clear, direct communication regarding fraud trends and strategy shifts to both technical and non-technical partners.

Ideally, you’d have:

• 5-8 years of experience in risk strategy and fraud analytics. You have a battle-tested track record of reverse-engineering adversarial patterns, dismantling complex fraud vectors, and driving highly analytical Trust & Safety or TPM programs.
• Expert proficiency in SQL skills. You must be highly comfortable extracting insights from large datasets in noisy, adversarial environments.
• An execution-driven mindset focused on delivering measurable results, not just theoretical analysis. You are comfortable working in ambiguity and taking ownership from data problems to operational solutions.
• Strong proficiency with AI coding assistants to accelerate data exploration and query writing.
• Deep understanding of how to balance aggressive fraud detection with marketplace growth. You make decisions based on what's right for the business, not what's convenient.

Nice to haves:

• Solid Python skills (e.g., Pandas, NumPy) for advanced data manipulation and scripting
• Experience working in marketplace or gig-economy platforms is a plus

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 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 sophisticated prompt engineering strategies optimized for customer-specific domains and data
• Build and maintain prompt libraries, templates, and best practices for customer use cases
• Conduct systematic prompt experimentation and A/B testing to improve model outputs
• Implement RAG (Retrieval Augmented Generation) systems and fine-tuning pipelines where appropriate

Technical Leadership & Collaboration

• Serve as the primary technical point of contact for strategic enterprise accounts
• Collaborate with customer data scientists, ML engineers, and software developers to ensure smooth integration
• Provide technical training and knowledge transfer to customer teams
• Work closely with Scale's product and engineering teams to translate customer needs into product improvements
• Document technical architectures, integration patterns, and best practices

Problem Solving & Innovation

• Debug complex technical issues across the entire stack, from data pipelines to model outputs
• Rapidly prototype solutions to unblock customers and prove out new use cases
• Stay current on the latest AI/ML research and tools, bringing innovative approaches to customer problems
• Identify opportunities for productization based on common customer patterns

Required Qualifications

• 4+ years of software engineering experience with strong fundamentals in data structures, algorithms, and system design
• Production Python expertise with experience in modern ML/AI frameworks (e.g., LangChain, LlamaIndex, HuggingFace, OpenAI API)
• Experience with cloud platforms (AWS, GCP, or Azure) and modern data infrastructure
• Strong problem-solving skills with the ability to navigate ambiguous requirements and rapidly iterate toward solutions
• Excellent communication skills with the ability to explain complex technical concepts to both technical and non-technical audiences

Preferred Qualifications

Agent Development Wiz

• Deep understanding of LLMs including prompting techniques, embeddings, and RAG architectures
• Experience building and deploying AI agents or autonomous systems in production
• Knowledge of vector databases and semantic search systems
• Contributions to open-source AI/ML projects

Infrastructure Guru

• Experience with containerization (Docker, Kubernetes) and CI/CD pipelines
• Experience using Terraform, Bicep, or other Infrastructure as Code (IaC) tools
• Previous work in a devops, platform, or infra role
• Familiarity with enterprise security, compliance, and governance requirements (SOC 2, GDPR, HIPAA)

Customer Product Whisperer

• Proven ability to work with customers in a technical consulting, solutions engineering, or product engineering role
• Domain expertise in verticals like finance, healthcare, government, or manufacturing
• Experience with technical enablement or teaching programs

Sample Projects

The following are some examples of the types of projects we’ve worked on with customers. All of these projects leverage customer data, integrate directly into customers’ existing systems, and are deployed on their infrastructure.

Deep Research for Due Diligence

For a global professional services firm, we developed a sophisticated deep research agent to assist in due diligence. This agent employs a multi-agent architecture for robust fact-checking, integrates several internal MCP tools, and processes complex, unstructured data sources. This solution reliably saves employees hundreds of hours weekly.

Churn Prediction

Working with a TelCo organization, we built a model utilizing customer data to predict churn likelihood. The system then curates personalized offers based on this prediction. This model was integrated into a "next best action" copilot, enabling call center agents to proactively surface relevant offers to customers, leading to a significant reduction in churn.

Data Extraction Voice Agent

We partnered with a healthcare organization to create a lifelike voice agent and avatar designed to gather unstructured health information from patients. Engineered for low latency, the agent adeptly manages conversational flow, adheres to safety guardrails, and efficiently handles data extraction. This automation saves the organization's nurses hundreds of hours each week.

Scale AI builds the data infrastructure that powers the world’s most advanced AI. We are the trusted data partner behind frontier model makers and enterprise AI teams — providing the high-quality training data, evaluation frameworks, and human-feedback systems that make models smarter, safer, and more capable.

Scale operates as a two-sided marketplace. On the demand side, our customers — leading AI labs and enterprises — need precisely labeled, expert-curated data to train and evaluate their models. On the supply side, we work with a global network of 500,000+ skilled contributors across 100+ countries who perform the complex annotation, evaluation, and data-generation tasks that fuel AI progress. Product Managers at Scale sit at the intersection of these two sides, shaping the systems, tooling, and experiences that make this marketplace work at unprecedented quality and scale.

We are hiring Product Managers across multiple teams within our GenAI organization. These roles span both demand-side products (the tools and platforms our customers interact with) and supply-side products (the systems that power our contributor ecosystem). Each role offers the opportunity to work on high-impact, technically complex problems at the frontier of AI — with dedicated engineering, design, and data science teams.

About the Role

• Scale’s GenAI platform is how the world’s leading AI companies — from frontier model labs to Fortune 500 enterprises — create the training data that makes their models best-in-class. As a PM here, you are building the systems that directly shape AI model quality.
• These roles are deeply cross-functional. You will work with dedicated engineering, design, and data science teams, as well as operations, finance, growth, and customer-facing stakeholders. The problems are technically complex, the pace is fast, and the impact is measurable.
• Whether you are on the demand side (shaping the products customers use to create and evaluate training data) or the supply side (building the systems that power our global contributor marketplace), you will own your product area end-to-end — from strategy to execution to instrumentation.
• Scale is a growth-stage company with the resources of a well-funded leader and the urgency of a startup. PMs here operate with significant autonomy, ship frequently, and are expected to be deeply analytical and hands-on.

Example Product Management Openings:

Task UX (Demand Side) — Own the end-to-end tasking product. You will define how tasks are designed, how contributors interact with multi-turn chat interfaces, and how in-task quality is measured and enforced across diverse conversational modalities. This is a critical surface area for training the next generation of models.

Multi-Dimensional Quality (Demand Side) — Own Scale’s MDQ measurement framework, the CoPilot assisted-annotation experience, and our data pipeline connectivity layer. You will drive the core data quality infrastructure that customers depend on — defining how quality is decomposed, measured, and surfaced, while building AI-assisted tooling that helps contributors produce higher-quality outputs faster.

Pay & Incentives (Supply Side) — This PM owns the payment and incentive systems that serve Scale’s global contributor base. You will ensure 500,000+ contributors across 100+ countries are paid accurately and on time, set pay rates methodically by skill and geography, and design incentive structures that balance cost efficiency, data quality, and contributor satisfaction. This role sits at the intersection of marketplace economics, global payments operations, and contributor experience.

You Will

• Set the product strategy and roadmap for your area, grounded in customer needs, data analysis, and business impact
• Develop and execute a data-driven product roadmap through close collaboration with senior leadership, engineering, operations, data science, analytics, and design
• Translate customer and internal-user needs into clear, well-defined functional and technical requirements backed by data analysis and deep understanding of your users
• Guide and interface closely with engineering and data teams to define scope, review and refine technical capabilities, prioritize projects for release, and identify new opportunities
• Build long-term instrumentation, monitoring, and evaluation capabilities for product performance tracking and insight generation
• Establish business cases and projected return on investment to identify and prioritize opportunities
• Partner with finance and business leaders to manage impact on the profitability and growth of the overall business
• Communicate product vision, strategy, and progress to executive stakeholders and cross-functional partners

Ideally, You’d Have

• 4–10 years of experience in Product Management in the tech industry, with scope appropriate to level (L4: 4–6 yrs, L5: 6–8 yrs, L6: 8–10+ yrs)
• Strong business acumen and analytical rigor, with demonstrated success driving products in ambiguous, high-growth environments
• Experience translating complex technical systems into clear product strategies — comfort engaging deeply with engineering and data science teams
• Excellent communication and stakeholder management skills, capable of influencing across technical and non-technical audiences
• Experience building products from the ground up and iterating through the scaling journey of a business
• Bachelor’s or advanced degree in a quantitative, engineering, or related discipline

Nice to Have:

• Experience in AI/ML, data infrastructure, or marketplace businesses
• Strong understanding of the AI landscape — model training workflows, data labeling, evaluation, and deployment
• Experience with global payment systems, contributor/gig-economy platforms, or trust & safety domains  
• Experience working at high-growth startups or scaling consumer/enterprise platforms

Scale AI accelerates the development of AI systems by providing the data, infrastructure, and tooling that power the most advanced models in the world. Our teams operate at the intersection of cutting-edge research, large-scale engineering, and real-world deployment, partnering with leading frontier labs, enterprises, and government agencies to push Generative AI into new capabilities and applications.

As AI rapidly evolves from static models to dynamic, agentic systems, Scale is building the foundational research, evaluation methodologies, and agent/RL infrastructure that will define this next era. You’ll join a high-impact research organization driving advances in large-language models, post-training, evaluation, and agentic/RL environments, helping shape how next-generation AI is built, measured, and deployed.

As a Research Scientist Manager, you will lead a world-class team of research scientists and engineers, define the research roadmap, and drive execution from early prototyping to deployment. You’ll thrive in a fast-moving environment, balancing deep technical leadership with people management, vision setting, and delivery.

You will:

• Lead, mentor and grow a team of research scientists and engineers working on GenAI research initiatives (e.g., evaluation, post-training, agents, RL environments).  
• Define and drive a multi-year research roadmap: identify key scientific questions, set milestones, allocate resources, and ensure rigorous execution.
• Collaborate cross-functionally with engineering, product, client-facing teams and external academic or industry partners to translate research into components, insights, and actionable outcomes.
• Communicate compellingly: publish research, present at conferences, engage in open-source contributions, and represent the team externally.
• Drive an inclusive, high-performing culture: help your team through technical challenges, provide growth opportunities, and attract top talent.
• Stay deeply connected to the research community, understanding major trends, and helping set them.
• Thrive in a high-energy, fast-paced startup environment and are ready to dedicate the time and effort needed to drive impactful results.

Ideally you'd have:

• 5+ years of hands-on research experience (PhD or equivalent preferred) in machine learning, deep learning, generative models, agent/rl systems or related domains.
• A strong track record of research excellence, including publications in top-tier ML/AI venues (NeurIPS, ICML, ICLR, ACL, etc.).
• Experience and track of recording in landing major research impacts in a fast-paced environment
• Experience leading or managing research teams. You’re excited to mentor, coach and develop talent.
• Excellent written and verbal communication skills. You are able to articulate research ideas and outcomes to both technical and non-technical stakeholders.

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. As a Staff Software Engineer, you will define and drive both the architectural roadmap and implementation of core platforms and software systems. You will be responsible for providing high-level vision and driving adoption across the engineering org for orchestration, data abstraction, data pipelines, identity & access management, and underlying cloud infrastructure.  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.

Impact and Responsibilities:

• Architectural Vision: You will drive the design and implementation of foundational systems, acting as a bridge between high-level business goals and technical goals.
• Cross-Functional Leadership: You will collaborate with cross-functional teams to define and drive adoption of the next generation of features for our AI data infrastructure.
• Technical Ownership: You are responsible for proactively identifying and driving opportunities for organizational growth, driving improvements in programming practices, and upgrading the tools that define our development lifecycle.
• Technical Mentorship: You will serve as a subject matter expert, presenting technical information to stakeholders and providing the guidance to elevate the engineering culture across the company.

Ideally you’d have:

• 8+ years of full-time engineering experience, post-graduation with specialities in back-end systems.
• Extensive experience in software development and a deep understanding of distributed systems and public cloud platforms (AWS preferred).
• Demonstrated a track record of independent ownership and leadership across successful multi-team engineering projects
• Possess excellent communication and collaboration skills, and the ability to translate complex technical concepts to non-technical stakeholders.
• Experience working fluently with standard containerization & deployment technologies like Kubernetes, Terraform, Docker, etc.
• Experience with orchestration platforms, such as Temporal and AWS Step Functions.
• Experience with NoSQL document databases (MongoDB) and structured databases (Postgres).
• Strong knowledge of software engineering best practices and CI/CD tooling (CircleCI, ArgoCD).

Nice to haves:

• Experience with data warehouses (Snowflake, Firebolt) and data pipeline/ETL tools (Dagster, dbt).
• Experience scaling products at hyper-growth startups.
• Excitement to work with AI technologies.

At Scale AI, we help leading enterprises turn AI from a promising capability into reliable systems that improve real workflows and deliver measurable business value. We are hiring a Senior Forward Deployed Data Scientist / Engineer to work directly with customers on ambiguous, high-impact problems at the intersection of data science, product development, and AI deployment.

This is not a traditional analytics role. On this team, data scientists do the core statistical and modeling work, but they also build real tools and products: evaluation explorers, operator workflows, decision-support systems, experimentation surfaces, and customer-specific AI/data applications that get used in production. In many cases, the data scientist builds the first usable version of the solution, proves value quickly, and helps drive it into a durable product or platform capability.

The right candidate is strong in first-principles problem solving, rigorous measurement, and technical execution. They know how to define metrics, design experiments, diagnose failures, and build systems that people actually use. They are also comfortable using modern AI-assisted development tools to prototype and iterate quickly without sacrificing reliability, observability, or judgment. Python and SQL matter in this role, but as execution fluency in service of building better products and making better decisions.

What you’ll do

• Partner directly with enterprise customers to understand workflows, operational pain points, constraints, and success criteria
• Turn ambiguous business and product problems into measurable solutions with clear metrics, technical designs, and deployment plans
• Design and build internal and customer-facing data products, including evaluation tools, workflow applications, decision-support systems, and thin product layers on top of data/ML systems
• Build end-to-end solutions across data ingestion, transformation, experimentation, statistical modeling, deployment, monitoring, and iteration
• Design evaluation frameworks, benchmarks, and feedback loops for ML/LLM systems, human-in-the-loop workflows, and model-assisted operations
• Apply rigorous statistical thinking to experimentation, causal inference, metric design, forecasting, segmentation, diagnostics, and performance measurement
• Use AI-assisted development workflows to accelerate prototyping and product iteration, while maintaining strong engineering discipline
• Diagnose failure modes across data quality, model behavior, retrieval, workflow design, and user experience, and drive fixes into production
• Act as the voice of the customer to Product, Engineering, and Data Science, using field learnings to shape roadmap and platform capabilities

What we’re looking for

• 5+ years of experience in data science, machine learning, quantitative engineering, or another highly analytical technical role
• Proven track record of shipping data, ML, or AI systems that delivered measurable business or product impact
• Exceptional ability to structure ambiguous problems, define the right success metrics, and translate them into executable technical plans
• Strong foundation in statistics, experimentation, causal reasoning, and measurement
• Experience building tools or products, not just analyses — for example internal workflow tools, evaluation systems, operator-facing products, experimentation platforms, or customer-specific applications
• Hands-on fluency in Python, SQL, and modern data/AI tooling; able to inspect data, prototype quickly, debug deeply, and productionize solutions that work
• Comfort using AI-assisted coding and development workflows to move from idea to usable product quickly
• Strong communication and stakeholder management skills; able to work effectively with customers, engineers, product teams, and executives
• High ownership and bias toward shipping in fast-moving environments with incomplete information

Preferred qualifications

• Experience in a forward deployed, solutions, consulting, or other client-facing technical role
• Experience designing evaluation frameworks for LLMs, retrieval systems, agentic workflows, or other AI-enabled products
• Experience with large-scale data processing and distributed systems such as Spark, Ray, or Airflow
• Experience with cloud infrastructure and modern data platforms such as AWS, GCP, Snowflake, or BigQuery
• Experience building lightweight applications, APIs, internal tools, or workflow software on top of data/ML systems
• Familiarity with marketplace experimentation, causal inference, forecasting, optimization, or advanced statistical modeling
• Strong product instinct and the judgment to know when the right answer is a model, an experiment, a tool, or a workflow redesign

What success looks like

Success in this role means taking a messy, high-stakes customer problem and turning it into a deployed system that is actually used. Sometimes that system is a model. Sometimes it is an evaluation framework. Sometimes it is an operator-facing tool or a lightweight data product that changes how decisions get made. In all cases, success is defined by measurable impact, rigorous evaluation, and reliable execution.

The Enterprise Account Executive (Healthcare & Life Sciences) will report to the Director of Enterprise GTM and own revenue growth across a portfolio of Scale AI’s most strategic healthcare and life sciences customers. This role is focused on selling complex, agentic AI solutions - autonomous workflows powered by LLMs and human-in-the-loop systems - into health systems, payers, pharma, biotech, and digital health organizations.

You will act as a strategic partner to clinical, operational, and technical leaders - helping them transform core workflows such as clinical documentation, prior authorization, revenue cycle, pharmacovigilance, clinical trials, medical affairs, and patient engagement through AI agents. This is a highly consultative, technical enterprise sales role requiring deep domain fluency, strong executive presence, and the ability to navigate regulatory, compliance, and multi-stakeholder complexity.

You will own the full customer lifecycle - from origination through close, deployment, and expansion - while quarterbacking cross-functional teams across Solutions Engineering, Product, Research, and Delivery to land and scale high-impact AI programs.

You Will:

• Own and expand relationships with leading healthcare and life sciences organizations (providers, payers, pharma, biotech), focusing on multi-year, strategic AI initiatives
• Sell agentic AI solutions by mapping Scale’s capabilities to high-impact workflows (e.g., clinical documentation, prior auth, revenue cycle, patient ops, clinical trials, drug safety, medical review)
• Build trusted relationships with executive stakeholders (CIO, CTO, CMIO, Chief Data/AI Officer, Heads of Clinical Ops, R&D, Commercial)
• Develop and execute multi-threaded account strategies that drive net-new revenue, expansion, and long-term platform adoption
• Lead complex deal cycles, including ROI modeling, business case development, and mutual close plans across new business, renewals, and expansions
• Partner closely with Solutions Engineering to design and land technically credible pilots, POVs, and production deployments
• Navigate healthcare-specific regulatory and compliance requirements (e.g., HIPAA, GxP, data governance, auditability) throughout the sales process
• Act as the voice of the customer internally - informing product roadmap, agent design, and vertical-specific solutions
• Maintain strong pipeline discipline, forecasting accuracy, and deal hygiene using Salesforce, Clari, and related tools
• Operate effectively in a fast-paced, cross-functional environment with high ownership and attention to detail

Ideally, You Will Have:

• 8–12+ years of enterprise sales experience, with significant focus on healthcare or life sciences (providers, payers, pharma, biotech, or digital health)
• Proven track record of closing and expanding large, complex, multi-million dollar deals in regulated environments
• Experience selling AI/ML, data platforms, or workflow automation technologies, with the ability to position agentic / LLM-driven solutions to both technical and non-technical stakeholders
• Strong understanding of key healthcare/life sciences workflows (e.g., clinical operations, revenue cycle, patient engagement, R&D, clinical trials, pharmacovigilance)
• Demonstrated success engaging executive stakeholders and building compelling ROI-driven business cases
• Familiarity with regulatory and compliance considerations (e.g., HIPAA, FDA/GxP, data privacy, model governance)
• Strong command of enterprise sales fundamentals, including account planning, multi-threading, and forecasting discipline
• Ability to navigate long, complex sales cycles with multiple stakeholders and competing priorities
• Excellent communication, storytelling, and executive presence
• High degree of ownership, intellectual curiosity, and a consultative, customer-first mindset

Nice to Haves:

• Experience selling agentic AI, LLM platforms, or automation solutions into healthcare or life sciences
• Background working with clinical, regulatory, or data organizations
• Familiarity with EHR systems, clinical data, or real-world evidence platforms
• Experience in high-growth or emerging technology environments

The Enterprise Account Executive (Financial Services) will report to the Director of Enterprise GTM and own revenue growth across a portfolio of Scale AI’s most strategic financial services customers and prospects. This role is focused on selling complex, agentic AI solutions -autonomous workflows powered by LLMs and human-in-the-loop systems - into large banks, insurers, asset managers, and fintechs.

You will operate as a strategic partner to senior executives across the business, technology, and risk organizations - helping them reimagine core workflows (e.g., underwriting, fraud detection, KYC, claims, research, and operations) through AI agents. This is a highly consultative, technical enterprise sales role requiring deep domain fluency, executive presence, and the ability to navigate regulatory, security, and multi-stakeholder complexity.

You will own the full customer lifecycle - from origination through close, deployment, and expansion - while acting as the quarterback across Solutions Engineering, Product, Research, and Delivery teams to land and scale high-impact AI programs.

You Will:

• Own and expand relationships with the largest financial services institutions (banks, insurers, capital markets, fintech), focusing on high-impact, multi-year AI transformations
• Sell agentic AI solutions by mapping Scale’s capabilities to mission-critical workflows (e.g., underwriting, fraud, compliance, customer ops, investment research)
• Build trusted relationships with executive stakeholders (CIO, CTO, Chief Data/AI Officer, Heads of Risk/Operations/Lines of Business) and guide enterprise AI strategy
• Develop and execute multi-threaded account plans that drive net-new revenue, expansion, and long-term platform adoption
• Lead complex deal cycles, including business case development, ROI modeling, and mutual close plans across new business, renewals, and expansions
• Partner deeply with Solutions Engineering to shape and land technically credible pilots, POVs, and production deployments
• Navigate regulatory, security, and procurement processes unique to financial services environments
• Act as the voice of the customer internally—informing product roadmap, agent design, and vertical-specific solutions
• Maintain a strong command of pipeline, forecasting, and deal hygiene using Salesforce, Clari, and related tools
• Operate with urgency and precision in a fast-paced, highly cross-functional environment

Ideally, You Will Have:

• 8–12+ years of enterprise sales experience, with significant focus on financial services (banking, insurance, capital markets, or fintech)
• Proven track record of closing and expanding large, complex, multi-million dollar enterprise deals within highly regulated environments
• Experience selling AI/ML, data platforms, or workflow automation technologies, with the ability to position agentic / LLM-driven solutions at a business and technical level
• Deep understanding of financial services workflows (e.g., underwriting, claims, fraud, KYC/AML, research, operations) and how technology transforms them
• Demonstrated success engaging and influencing executive stakeholders, including building and delivering compelling business cases and ROI narratives
• Strong command of enterprise sales methodology, including account planning, multi-threading, and disciplined forecasting
• Ability to navigate ambiguity, long sales cycles, and complex stakeholder landscapes with high ownership and resilience
• Excellent communication and storytelling skills across both technical and non-technical audiences
• High level of business acumen, technical curiosity, and a consultative, customer-first mindset

Nice to Haves:

• Experience selling agentic AI, LLM platforms, or automation solutions into financial services
• Background working with or alongside risk, compliance, or data organizations within large enterprises
• Familiarity with regulatory considerations (e.g., model risk management, auditability, data privacy) in AI deployments
• Prior experience in high-growth or emerging technology environments

About the Role

The Director of Business Systems will be responsible for building real depth across Finance, GTM, Operations, and People systems, connecting these capabilities into a powerful, AI-integrated backbone.

You are a builder-first leader who will blend enterprise architecture with cutting-edge AI automation. Your goal is to eliminate fragmentation and enable every function to move faster by deploying internal AI agents that reduce manual work and surface actionable insights. You will lead the charge in making our internal operations as sophisticated as the external products we build.

Key Responsibilities

• Enterprise Application Strategy: Own the full lifecycle of our application ecosystem, including ERP (Finance), CRM (GTM), HRIS (People), and specialized AI tools. Ensure these systems converge into a secure, scalable backbone.
• AI Agent Deployment: Identify opportunities to replace manual workflows with AI/LLM-powered agents. Build and manage "internal agents" that automate forecasting, revenue capture, and employee self-service.
• Cross-Functional Partnership: Serve as the primary technology partner to the leadership team. Align system roadmaps with departmental goals to ensure seamless data flow from production to the back office.
• Operational Excellence: Mature our core systems by establishing disciplined change management, clear data governance, and measurable SLAs. Stabilize environments to support audit and regulatory requirements.
• Team Leadership: Lead a high-impact team that fosters a culture of curiosity, speed, and user-centricity.

Ideally, you have:

• 10+ years of experience leading business systems or enterprise applications in a fast-paced, high-growth environment.
• Technical Depth: Strong functional understanding of Salesforce (or equivalent CRM), NetSuite (or equivalent ERP), and Workday (or equivalent HRIS).
• AI/Automation Mindset: Proven track record of designing and deploying AI/LLM-powered workflows or agentic systems to improve business efficiency.
• Architecture Skills: Ability to design scalable data flows and APIs that link disparate SaaS tools into a cohesive ecosystem.
• Stakeholder Mastery: Experience influencing C-level executives and translating complex technical needs into business outcomes.
• Skilled in Python or SQL to personally audit or prototype automation logic.
• Extensive experience and In depth knowledge of the functionality of the ERP modules with emphasis on Sales – Order to Cash & Sales Audit, Purchasing – Direct & Indirect and Finance - General Ledger, AP & AR, Procure to Pay, Sales Audit, Fixed Assets, International Consolidations & Reporting
• Experience with GTM systems such as, HubSpot, Outreach, Clari, CPQ (e.g., Salesforce CPQ), and similar tools.

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

AI is becoming vitally important in every function of our society. At Scale, our mission is to accelerate the development of AI applications. For 9 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 investment from Meta, we are doubling down on building out state of the art post-training algorithms to reach the performance necessary for complex agents in enterprises around the world. 

The Enterprise ML Research Lab works on the front lines of this AI revolution. We are working on an arsenal of proprietary research, tools, and resources that serve all of our enterprise clients. As MLRE on the Data Foundation team, you’ll work on cutting edge research to define the data flywheel that makes the whole machine move. This includes research around synthetic environments from task definitions, building agents for trace analysis, and contributing to a cutting edge framework that automatically hill-climbs agent-building from an eval set. This will involve creating best-in-class Agents that achieve state of the art results through a combination of post-training + agent-building algorithms.

If you are excited about shaping the future of the modern GenAI movement, we would love to hear from you!

You will: 

• Build synthetic data pipelines to generate enterprise environments to use for RL post-training
• Create agents to convert traces from production into actionable insights to use to improve agents
• Contribute to our agent building product which can construct other agents using coding agents + proprietary algorithms
• Train state of the art models, developed both internally and from the community, to deploy to our enterprise customers. 

Ideally you’d have:

• 3+ years of building with LLMs in a production environment
• Clear experiences with constructing high quality data to use to improve an LLM/Agent
• Publications in top conferences such as NEURIPS, ICLR, or ICML within the last two years
• PhD or Masters in Computer Science or a related field

Scale AI is looking for an Internal Communications Senior Manager to join our Communications team. Reporting to the Internal Communications Lead, you will be a key driver in building and scaling a world-class internal comms function that connects every employee to Scale's mission, leadership vision, and business milestones. This is a high-impact, cross-functional role that will shape how nearly every team at Scale understands and rallies around company goals.

You will:

• Own and expand internal communications across all business units, building structured programs that help leaders engage and align their teams
• Identify gaps in the current internal comms landscape and design net-new programs, from concept through execution, that meet the evolving needs of a fast-growing, cross-functional organization.
• Partner closely with business unit leaders and chiefs of staff to develop and execute their communications strategies, including AMAs, leadership updates, and mission-critical announcements
• Drive the strategy and execution of company wide channels including all-hands meetings, AMAs, internal newsletters, and Slack channels with the goal of ensuring employees feel informed and connected to Scale's direction
• Develop a cohesive internal communications framework that ladders up to CEO and executive messaging, helping employees understand business performance, company milestones, and strategic priorities
• Act as a strategic advisor to senior leaders on how to communicate with and inspire their teams, improving leader visibility and employee engagement across the organization
• Build and maintain measurement frameworks (e.g., pulse surveys, engagement metrics) to assess program impact and continuously improve internal comms effectiveness
• Collaborate with the broader Communications team on crisis, policy, and corporate storytelling as needed, ensuring internal and external narratives are aligned

Ideally you'd have:

• 6+ years of experience in internal communications, with a proven track record of building and scaling internal comms programs at a fast-growing technology company
• Demonstrated experience advising and partnering with senior leaders and executives on communications strategy, with the ability to influence without authority
• Strong program management skills and the ability to build repeatable, scalable processes across a large, cross-functional organization
• Exceptional written and verbal communication skills, with the ability to craft compelling narratives that resonate with diverse internal audiences

Nice to haves:

• Experience working in a high-growth technology company
• Familiarity with internal comms tools, platforms (e.g., Slack, intranet systems, survey tools) programming, and data-driven approaches to measuring communication effectiveness
• Experience supporting CEO or executive-level communications in a fast-paced environment

Please note that in order to maintain integrity to our Scale titling philosophy, we do not internally use titles such as “senior,” but have levels to reflect seniority. Our Talent Acquisition team works closely with our employees to provide them the opportunity to grow their careers and demonstrate the scope of work in other ways aside from job titles. If you have further questions, please direct them to your recruiter and/or hiring manager, who can provide more insight.

Scale AI accelerates AI development by providing high-quality training data and infrastructure. We work with leading organizations to solve complex problems, enabling them to build transformative AI models. Join our team to shape the future of AI and push the boundaries of innovation.

We are looking for a versatile Senior Motion Designer to join the Brand Studio at Scale AI. This is an exciting opportunity to help evolve Scale's brand, creating dynamic visual narratives for brand storytelling, translating creative direction into animated content and videos across a wide range of initiatives, including marketing campaigns, events, creative content development, and cross-functional collaborations. The ideal candidate is scrappy, thrives in a fast-paced, dynamic environment, is willing to experiment, and has exceptionally strong design fundamentals.

You will:

• Creative Execution: Lead the end-to-end production of high-fidelity motion graphics, from initial concept to final rendering and delivery
• Experimental R&D: Dedicate time to research and development of new design concepts, experimenting with emerging motion trends and technologies to keep the brand at the forefront of the AI industry
• Process Innovation: Develop and optimize motion workflows, including the integration of generative AI tools to improve team efficiency and output quality
• Design Excellence: Apply a high degree of taste and rigorous design fundamentals to all experimental work, ensuring that even the most "scrappy" or innovative explorations maintain brand integrity 
• Narrative Storytelling: Translate complex technical data and AI concepts into compelling visual narratives that resonate with both developer communities and executive stakeholders

Ideally you'd have:

• Experience: 5+ years of professional experience in motion design or creative production, ideally within a high-growth technology company, world-class agency, or culturally-defining brand
• Design Fundamentals: Exceptional command of typography, color theory, and composition
• Adaptability: Proven ability to thrive in "scrappy" and ambiguous environments, managing rapid-fire R&D alongside long-term strategic projects
• Collaborative Spirit: Experience working in multidisciplinary teams and a track record of fostering a culture of continuous learning and mentorship

Nice to haves:

• Experience in node based motion software such as TouchDesigner, Cavalry
• 3D software experience - Cinema 4D, Blender, or Houdini
• Generative AI tooling - Kling, Runway, Midjourney, Flora, Krea, etc. 
• Background in creative production
• Experience working with global teams and managing remote collaborations

Why Join Scale AI?

• Work on cutting-edge AI projects that shape the future of technology
• Join a talented, collaborative team that values creativity and innovation
• Competitive compensation and benefits

How to Apply

If you are excited about contributing to the future of AI and believe you have the skills and experience to excel as a Senior Motion Designer at Scale AI, we’d love to hear from you! Apply today with your resume and a brief cover letter.

Please note that in order to maintain integrity to our Scale titling philosophy, we do not internally use titles such as “senior,” but have levels to reflect seniority. Our Talent Acquisition team works closely with our employees to provide them the opportunity to grow their careers and demonstrate the scope of work in other ways aside from job titles. If you have further questions, please direct them to your recruiter and/or hiring manager, who can provide more insight.

Scale AI is seeking a highly technical and strategic Staff / Senior Staff Machine Learning Engineer to act as the Tech Lead (TL) for our next generation of deep research agents for the Enterprise. This high-impact role will drive the technical direction and oversight for Deep Research Agent Development, translating cutting-edge research in Generative AI, Large Language Models (LLMs), and Agentic Frameworks into robust, scalable, and high-impact production systems that enhance enterprise operations, analytics, and core efficiency.

The ideal candidate thrives in a fast-paced environment, has a passion for both deep technical work and mentoring, and is capable of setting a long-term technical strategy for a critical domain while maintaining a strong, hands-on delivery focus.

Responsibilities

Technical Leadership & Vision

• Set the Technical Roadmap: Define and own the technical strategy, architecture, and roadmap for Deep Research Agents for the Enterprise, ensuring alignment with Scale AI’s overall AI strategy and business goals.
• Drive Breakthrough Research to Production: Lead the end-to-end development, from initial research to production deployment, to landing on customer impact, with a focus on integrating diverse data modalities.
• Core Agent Capabilities Development:
• Advanced Knowledge Retrieval: Architect and implement state-of-the-art retrieval systems to ensure the agents provide accurate and comprehensive answers from public and proprietary data sources from enterprises.
• Data analysis: Design and champion the development of data analysis agents that accurately translate complex natural language queries into executable SQL/code against diverse enterprise data schemas.
• Multimodal Intelligence: Lead the integration of Multimodal AI capabilities to process and extract structured information from visual documents, tables, and forms, enriching the agent's knowledge base.
• Architecture & Design: Design and champion highly scalable, reliable, and low-latency infrastructure and frameworks for building, orchestrating, and evaluating multi-agent systems at enterprise scale.
• Technical Excellence: Serve as the technical authority for the team, leading design reviews, defining ML engineering best practices, and ensuring code quality, security, and operational excellence for all agent systems.

Team Leadership & Mentorship

• Lead and Mentor: Technically lead and mentor a team of Machine Learning Engineers and Research Scientists, fostering a culture of innovation, rigorous engineering, rapid iteration, and technical depth.
• Recruiting & Growth: Partner with management to hire, onboard, and grow top-tier talent, helping to shape the long-term structure and capabilities of the team.
• Cross-Functional Influence: Collaborate effectively with Product Managers, Data Scientists, and other engineering/science teams to translate ambiguous, high-level business problems into concrete, executable technical specifications and impactful agent solutions.

Basic Qualifications

• Bachelor's degree in Computer Science, Electrical Engineering, a related field, or equivalent practical experience.
• 8+ years of experience in software development, with at least 6 years focused on Machine Learning, Deep Learning, or Applied Research in a production environment.
• 2+ years of experience in a formal or informal Technical Leadership role (Team Lead, Tech Lead) with a focus on setting technical direction for a domain.
• Deep expertise in Generative AI and Large Language Models (LLMs).
• Demonstrated experience designing, building, and deploying AI Agents or complex Agentic systems in production at scale.
• Experience with large-scale distributed systems and real-time data processing.

Preferred Qualifications

• Advanced degree (Master's or Ph.D.) in Computer Science, Machine Learning, or a related quantitative field.
• Demonstrated experience designing and deploying production-grade Text-to-SQL systems, including handling complex schema linking and query optimization.
• Practical experience with Multimodal AI, specifically integrating OCR and vision-language models for document intelligence and structured data extraction from images/forms.
• Proven experience in one or more relevant deep research areas: Reinforcement Learning (RL), Reasoning and Planning, Agentic Systems.
• Experience with vector databases and advanced retrieval techniques.
• A track record of publishing research papers in top-tier ML/AI conferences (e.g., NeurIPS, ICML, ICLR, KDD).
• Excellent written and verbal communication skills, with the ability to articulate complex technical vision to executive stakeholders and technical peers.
• Experience driving cross-team technical initiatives that have delivered significant business impact.

We are seeking a Senior Security Engineer with a specialty in Detection and Incident Response to join our Security Engineering team. This role sits at the intersection of security operations and software engineering — you won't just investigate incidents, you'll build the systems that detect, contain, and prevent them. You will design and ship high-precision detections across cloud services and enterprise SaaS, develop automation that shortens response timelines, and mature the telemetry pipelines that make it all possible. Your ability to write production-quality code is just as important as your ability to triage an alert.

You will structure investigations, analyze root causes, and clearly communicate the significance of security incidents, their impact, and recommended remediation steps — but you'll also turn those findings into durable engineering improvements: better detections, tighter schemas, and smarter automation.

You will:

• Engineer, test, and deploy detection logic across cloud and enterprise environments, treating detections as software with version control, peer review, and measurable performance.
• Build and maintain incident response automation, runbooks, and tooling that reduce containment timelines without sacrificing developer velocity.
• Mature telemetry pipelines through improved schema design, normalization, enrichment, and quality checks that reduce false positives and increase signal fidelity.
• Perform digital incident investigations to identify and contain potential security breaches.
• Conduct digital forensics and malware analysis to understand attack vectors and adversary methodologies.
• Integrate alerting with messaging and ticketing systems to enable fast, traceable response workflows.
• Partner cross-functionally with IT, security, and engineering teams to harden identity and access patterns, close logging and forensics gaps, and implement maintainable guardrails that scale with the organization.
• Utilize threat intelligence platforms to improve hunting, detection, and response workflows.
• Clearly explain the significance and impact of incidents, providing actionable recommendations to both technical and non-technical stakeholders.

Ideally, you'd have:

• • 5+ years of experience in Detection Engineering, Incident Response, or Security Operations, with a strong emphasis on building and shipping security tooling and automation.
  • Proficiency in at least one programming language (e.g., Python, Go) and comfort writing production-grade code — not just scripts.
  • Hands-on experience designing or improving detection pipelines, SIEM content, and alerting workflows in cloud-native environments.
  • Practical experience with SIEM, EDR, and SOAR tools, with a preference for candidates who have built integrations or extended these platforms programmatically.
  • Strong understanding of modern cyber threats, common attack techniques, and adversary TTPs.
  • Familiarity with digital forensics tools and malware analysis techniques.
  • Experience with cloud-native environments (e.g., AWS, GCP, Azure) and the security telemetry those environments generate.
  • Exposure to threat intelligence platforms and integrating intel into detection and investigation workflows.
  • Strong communication skills, with the ability to translate complex security findings into clear business impact.
  • Relevant security certifications (e.g., GCIH, GCFA, GCIA, CISSP, GDSA) are a plus.

Scale seeks a business-minded Director and Associate General Counsel, Compliance to lead Scale’s corporate compliance program. This role will set the legal standards, governance model, and escalation framework for the program, working closely with cross-functional partners to translate that guidance into practical workflows.

This is a high-impact role for a lawyer who combines strong legal judgment with practical program execution in a fast-moving, high-visibility business.

You Will:

• Advise on anti-bribery and anti-corruption, conflicts of interest, gifts and entertainment, third-party risk, and other sensitive corporate compliance matters.
• Lead or support privileged compliance investigations, remediation, and escalations, coordinating across Legal and with outside counsel where matters involve potential litigation or enforcement risk.
• Develop practical compliance policies, workflows, training, and reporting processes that support Scale’s growth and IPO-readiness.
• Mature Scale’s Enterprise Risk Management process, including risk assessment methodology, risk register governance, mitigation tracking, and leadership reporting.
• Set legal standards for compliance operations, including hotline triage, sensitive matter review, policy governance, training requirements, and remediation escalation.
• Partner across Legal, GRC, Security, Product, Engineering, Finance, People, Public Sector, and other business teams on compliance and IPO-readiness.
• Represent Scale’s corporate compliance function with internal and external stakeholders, including customers, auditors, partners, and regulators.

Ideally, you’d have:

• JD and active bar membership in at least one U.S. jurisdiction.
• 10+ years of legal experience across corporate compliance, investigations, regulatory counseling, GRC, internal controls, or related areas.
• Experience building or scaling compliance programs in high-growth technology or similarly complex environments.
• Strong experience with anti-bribery and anti-corruption, conflicts of interest, third-party risk, hotline governance, and privileged investigations.
• Experience maturing ERM, policy governance, training, remediation tracking, risk reporting, and IPO-readiness or public-company compliance.
• Strong judgment and communication skills, with the ability to work effectively across legal, technical, operational, and executive stakeholders.

Nice to haves:

• Experience with AI governance or regulation.
• Familiarity with government contractor compliance, export controls, or industrial security.
• Experience with multinational compliance programs, including Europe, the Middle East, Asia, and Latin America.

Scale GP is Scale’s enterprise Generative AI platform, providing APIs and infrastructure for knowledge retrieval, inference, evaluation, and intelligent automation. We power mission-critical workflows for leading enterprises by helping teams turn complex data and models into reliable, production-ready AI systems.

We’re forming a new Agentic Data Products team focused on building the next generation of agent-powered tools that ground AI in real operational workflows. Our goal is to help enterprises demystify their data layers and deploy intelligent, agentic systems that can reason over data, take action, and deliver measurable outcomes.

This is a 0→1 build team. We’re looking for a sharp, product-minded Senior Engineer who thrives in ambiguity, moves quickly, and enjoys building new 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 major full-stack product areas, driving features from concept and design through production deployment
• Build intuitive, high-performance frontend experiences using React + TypeScript
• Develop reliable backend services in Python, working with distributed systems, data pipelines, and AI/ML infrastructure
• Integrate LLMs, vector databases, and agentic frameworks to power intelligent workflows and decision-making systems
• Ship quickly through tight experimentation loops while maintaining high quality and reliability
• Help define the technical direction and architecture of a brand-new team and product surface
• Adapt across the stack and learn new tools as needed to solve real problems end-to-end

Ideal Experience

• 5+ years of full-time software engineering experience
• 0-1 product build experience 
• Familiarity with LLMs, embeddings, vector databases, or modern AI data products/tools 
• Experience with distributed systems and cloud-based architectures
• Prior experience mentoring or leading team 

What We Value

• Strong product intuition and customer empathy
• Bias toward action and rapid iteration
• Ownership mentality — you see problems through to outcomes
• Comfort collaborating across engineering, product, data science, and applied AI
• Excitement about building agentic systems that make AI genuinely useful in the real world

Please note that in order to maintain integrity to our Scale titling philosophy, we do not internally use titles such as “senior,” but have levels to reflect seniority. Our Talent Acquisition team works closely with our employees to provide them the opportunity to grow their careers and demonstrate the scope of work in other ways aside from job titles. If you have further questions, please direct them to your recruiter and/or hiring manager, who can provide more insight.

Scale AI’s Public Sector business is growing quickly as government agencies adopt AI to support critical national security, defense, and public sector missions. We’re looking for a hands-on Field Engineering Manager on the front lines leading a team of our field engineering efforts for our federal AI projects, having the opportunity to meaningfully impact millions of dollars in revenue by working closely with our largest public sector customers and ensuring that they become passionate, lifelong Scale customers. This role is ideal for someone who thrives in technical environments, enjoys managing teams while staying close to the code, and wants to work on meaningful problems that impact real world operations across the U.S. government. 

Field Engineers are software engineering generalists who enjoy working with clients directly, taking ambiguous requirements and issues, and quickly designing and building production-grade solutions in close collaboration with the Product, Engineering, and Delivery teams. Field Engineers are experts on Scale's products and codebase, and have general technical knowledge on GenAI systems, APIs, networking, and data engineering. Field Engineers are strong relationship builders, great project managers, and always fun to work with. You’ll play a critical role in delivering technical solutions—all while helping your team grow and execute.

You’ll split your time between technical planning and execution (50%) and people management and team development (50%), leading a team of 6-8 engineers. You’ll work cross-functionally with product, engineering, security, and delivery teams to ensure our engineering efforts meet complex federal compliance, security, and performance needs.

Day to day:

• 50% Field engineering - customer engagement, technical development and delivery 
• 50% Managing a growing team

You will:

• Recruit a high-performing engineering team. 
• Drive engineering productivity. Provide guidance, mentorship, and technical leadership to a team of customer facing engineers working on Generative AI projects. 
• Collaborating with cross-functional teams to define, design, and execute strategic roadmap based on customer needs.
• Work directly with customers to understand their problems and translate those into custom workflows within Scale’s platform.
• Be open to ~25% travel or relocation to a key customer geographic location.
• Collaborate with cross-functional teams to define the vision for backend solutions, ensuring they meet the unique needs of government agencies operating in secure environments.
• Implement end-to-end data integrations, syncing customer’s data to Scale’s platform and back.
• Participate actively in customer engagements, working closely with stakeholders to understand requirements and deliver innovative solutions.
• Lead end-to-end technical delivery of custom workflows from scoping to development to testing to implementation
• This role will require an active TS/SCI security clearance or the ability to obtain a security clearance.

Ideally you’d have:

• 5+ years of full-time engineering experience, post-graduation.
• 2+ years of prior engineering management or equivalent experience and previously managed an engineering team.
• Track record of success as a hybrid customer facing engineer, forward deployed software engineer, and ability to quickly adapt to different roles.
• Prior experience developing with Python and JavaScript, or other modern software languages. 
• 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) is a plus.
• Linux experience: Understanding of shell scripting, operating systems, etc.
• Networking experience: Understanding of networking technologies, configuration  (ports, protocols, etc) is a plus.
• Data Engineering: Knowledge of ETL (Extract, Transform, Load) processes and experience in building data pipelines to integrate and process diverse data sources. Understanding of data modeling, data warehousing, and data governance principles.
• Problem Solving: Strong analytical and problem-solving skills to understand complex challenges and devise effective solutions. Ability to think critically, identify root causes, and propose innovative approaches to overcome technical obstacles.
• Understand unique DoD and USG constraints when it comes to technology.

Senior Software Engineer, Platform — Connectivity

The Connectivity team owns the core platform that enables Scale to continuously generate, evaluate, and deliver high-quality training data to our customers. Our systems sit at the center of Scale’s data and AI infrastructure, powering large-scale workflows while supporting frontier AI capabilities such as multi-modality, long-horizon reasoning, and agentic behavior.

We’re looking for a senior engineer with deep experience building robust platforms, someone who brings strong architectural judgment, a bias toward correctness and reliability, and the ability to design systems that scale and evolve cleanly over time. This is a backend-heavy role with full-stack expectations and significant ownership from design through long-term operation.

What You’ll Do

• Design and own foundational platform systems that support scalable data generation, evaluation, and bespoke customer delivery across Scale’s ecosystem.
• Architect extensible, production-grade services that can support frontier AI workflows, including multi-modal inputs, long-running processes, and agentic orchestration.
• Build and operate distributed systems at scale, with strong guarantees around correctness, reliability, observability, and cost efficiency.
• Integrate with public LLM APIs and AI services, designing abstractions that are resilient to model churn, latency variability, and evolving usage patterns.
• Design and maintain data transformation and processing systems, supporting complex schema evolution, customization, and high-throughput workloads.
• Partner closely with infrastructure, product, and customer-facing teams to define requirements, shape technical direction, and deliver seamless integration experiences for customers.
• Lead multi-quarter technical initiatives, including authoring and driving a 6+ month technical roadmap for major platform investments.
• Apply strong engineering judgment in ambiguous problem spaces, balancing speed with long-term maintainability and operational excellence.
• Raise the quality bar through thoughtful system design reviews, rigorous code reviews, and mentorship grounded in real-world production experience.

Ideal Experience

• 7+ years of professional software engineering experience, with a strong background in building and operating large-scale, production-grade platforms.
  
  
• Deep expertise in distributed systems and cloud-native architectures, including Kubernetes, microservices, event-driven systems, caching, and production databases.
  
  
• Proven ability to lead multi-quarter technical initiatives, work effectively across cross-functional teams, and apply strong architectural judgment in ambiguous environments.
  
  
• Preferred: Experience integrating with public LLM APIs and designing systems that handle scale, reliability, latency, and cost tradeoffs.
  
  

Preferred: Experience building or operating data processing and transformation systems supporting complex workflows and evolving schemas.

Scale AI’s Public Sector business is growing quickly as government agencies adopt AI to support critical national security, defense, and public sector missions. We are looking for a Mission Software Engineering Manager to join our dynamic Federal Engineering team. As a part of this team, you will play a critical role in supporting Scale’s government customers by scoping and developing onsite solutions. Our scalable, high-performance platform is the foundation for these customer solutions, and your expertise will be instrumental in designing and implementing systems that can handle interactions with existing customer systems to help our products integrate into existing customer workflows.  

You will:

• Recruit a high-performing engineering team. 
• Drive engineering productivity. Provide guidance, mentorship, and technical leadership to a team of engineers working on Generative AI projects. 
• Collaborating with cross-functional teams to define, design, and execute strategic roadmap.
• Work directly with customers to understand their problems and translate those into features in Scale’s platform.
• Be open to ~25% travel or relocation to a key customer geographic location.
• Collaborate with cross-functional teams to define and execute the vision for backend solutions, ensuring they meet the unique needs of government agencies operating in secure environments.
• Implement end-to-end data integrations, syncing customer’s data to Scale’s platform and back.
• Deploy and maintain Scale software at customer sites
• Develop customer requested features and work closely with them to ensure that they win customer love.
• Build robust and reliable backend systems that can serve as standalone products, empowering customers to accelerate their own AI ambitions.
• Participate actively in customer engagements, working closely with stakeholders to understand requirements and deliver innovative solutions.
• This role will require an active TS/SCI security clearance or the ability to obtain a security clearance.

Ideally you’d have:

• 5+ years of full-time engineering experience, post-graduation
• 2+ years of prior engineering management or equivalent experience and has managed an engineering team.
• Track record of success as a hybrid customer facing engineer, forward deployed software engineer, and ability to quickly adapt to different roles.

• Prior experience developing with Python and JavaScript, or other modern software languages. Familiarity with Node and React is a plus.
• 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) is a plus
• Linux experience: Understanding of shell scripting, operating systems, etc
• Networking experience: Understanding of networking technologies, configuration  (ports, protocols, etc) 
• Data Engineering: Knowledge of ETL (Extract, Transform, Load) processes and experience in building data pipelines to integrate and process diverse data sources. Understanding of data modeling, data warehousing, and data governance principles
• Problem Solving: Strong analytical and problem-solving skills to understand complex challenges and devise effective solutions. Ability to think critically, identify root causes, and propose innovative approaches to overcome technical obstacles
• Understand unique DoD and USG constraints when it comes to technology

The Head of Legal Operations and Chief of Staff acts as the primary strategic partner to the General Counsel, ensuring the department’s operational goals are in lockstep with the company’s broader vision. This role is responsible for turning the Legal & Governance, Risk, and Compliance (GRC) team into a high-performing business unit–- providing the processes, technology, and data insights necessary to enable a 30+-person global team. You will lead a 2-person Legal Operations team, focusing on high-level strategy and enabling your team to lead their respective workstreams with high degrees of autonomy and accountability.

You will:

• Strategic Partnership (Chief of Staff): Partner with the GC and Legal Leadership (Commercial, Corporate, Litigation, Product, GRC, and Public Sector) to define and execute long-term strategy. Own operational planning cycles, including the OKR process, roadmap development, and All-Hands meetings, to ensure cross-functional alignment and maximize the team’s impact.
• Team Leadership & Mentorship: Manage and mentor the Contracts Manager and Legal Program Manager, empowering them to lead their functional areas with high autonomy. Provide mentorship on a dotted-line basis to subject matter experts (e.g., Corporate Paralegal, Privacy Program Manager), ensuring process consistency and high-standard workstreams across the broader Legal & GRC organization.
• Success Management: Design and own the reporting framework for tracking departmental success. Oversee the development of automated dashboards that provide real-time progress against goals, utilizing AI to synthesize data into actionable insights for the GC and Legal Leadership Team.
• Legal Finance & Vendor Strategy: Manage the global Legal budget, forecasting, and accruals. While partnering with the Procurement team for general needs, you will directly lead the strategy for Legal-specific vendors, including outside counsel and legal tech providers. Drive outside counsel management strategy, emphasizing data-driven performance reviews and the negotiation of arrangements that optimize litigation and specialty matter spend.
• Process & Technology: Maintain and optimize a world-class Legal & GRC tech stack (e.g., CLM, e-billing, and litigation tools). Drive business velocity by designing streamlined intake and triage systems for Product and Engineering teams and implementing practical, automated workflow solutions.
• Risk & Litigation Operations: Direct the litigation technology strategy, including the legal hold lifecycle and e-discovery workflows, to ensure defensible compliance in partnership with IT and Security. Develop and maintain strategic risk registers that provide the GC, Legal Leadership, and executive leadership with a clear, data-driven view of the company’s risk landscape.

Ideally you'd have:

• Experience: 10+ years of professional experience, with a solid background in Legal Operations, Strategy, or Management Consulting in a high-growth environment.
• Education: Bachelor’s degree required. An Engineering degree, MBA, or JD is a significant plus.
• Technical Proficiency: Practical experience with legal technology (e.g., Ironclad, Brightflag) and a curiosity for how AI/automation can solve routine legal hurdles. Familiarity with litigation-specific tools (e.g., Logikcull, Relativity, or specialized legal hold software) is highly preferred.
• Analytical & Risk Modeling: Ability to design and maintain strategic risk registers and financial models. You can translate raw data from various workstreams into a cohesive risk landscape (e.g., impact vs. likelihood heatmaps) that informs executive decision-making. Partner with the GC and Legal Leadership to model potential exposure, manage entity-related risks, and inform corporate reserves.
• Mindset: A pragmatic, "get it done" attitude. You can navigate ambiguity, represent the GC in executive forums, and prioritize the tasks that provide the most value to the department.
• Communication: Exceptional ability to translate operational data into clear, concise updates for the GC and executive leadership.

AI is becoming vitally important in every function of our society. At Scale, our mission is to accelerate the development of AI applications. For 9 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 investment from Meta, we are doubling down on building out state of the art post-training algorithms to reach the performance necessary for complex agents in enterprises around the world. 

The Enterprise ML Research Lab works on the front lines of this AI revolution. We are working on an arsenal of proprietary research, tools, and resources that serve all of our enterprise clients. As an Agent MLRE, you will be working on applying our Agent RL Training + Building algorithms to real life enterprise datasets across our clients + benchmarks. This will involve creating best-in-class Agents that achieve state of the art results through a combination of post-training + agent-building algorithms.

If you are excited about shaping the future of the modern GenAI movement, we would love to hear from you!

You will: 

• Train state of the art models, developed both internally and from the community, to deploy to our enterprise customers. 
• Research cutting edge algorithms to integrate directly into our training stack.
• Build agents that leverage our proprietary agent-building algorithms to automatically hill climb datasets – including defining highly performant tools, multi-agent systems, and complex rewards.

Ideally you’d have:

• 1-3 years of building with LLMs in a production environment
• Experience with post-training methods like RLHF/RLVR and related algorithms like PPO/GRPO etc.
• Publications in top conferences such as NEURIPS, ICLR, or ICML within the last two years
• PhD or Masters in Computer Science or a related field

At Scale, we develop reliable AI systems for the world’s most important decisions. The Brand Experience manages all aspects of Scale’s brand, including the company’s front door scale.com. It’s often a prospect's first real experience with our brand and what we build. The Web Experience Manager will lead our small team of developers and designers, and take full ownership of the strategy, operations, and quality of our digital presence.

This role sits at the intersections of brand, engineering, marketing, and design. You'll translate priorities from cross-functional teams into a clear roadmap, hold a high bar for quality, expertly leverage modern AI web tools, and make sure the team has the clarity and support they need to do their best work. You're a people-first leader with enough technical depth to make good calls quickly.

You will: 

Lead the Team

• Own the web roadmap by maintaining, prioritizing, and communicating clearly so the team is always working on what matters most
• Manage and develop a lean team of web developers and designers by supporting career growth, handling resource allocation, and proposing and scoping new initiatives
• Serve as the connection point between the web team and cross-functional partners (Brand, Marketing, and Product) by translating priorities into a well-sequenced backlog, protecting the team's focus

Own Quality & Reliability

• Own the quality of everything that ships by building the testing and review framework, managing deployments, and setting the standard for what "done" means
• Design and run the planning around urgent issues; set clear response-time SLAs for site performance and internal support requests and hold to them
• Build the systems to keep marketing sites secure, performant, and compliant 24/7
• Lead post-mortems after incidents by coordinating the fix, communicating status to stakeholders, documenting learnings with rigor, and adjusting the roadmap accordingly

Manage Our Stack

• Oversee Scale's integrations on web properties by monitoring for performance, output quality, and consistency
• Manage relationships with web vendors, internal security, and IT teams
• Regularly audit the AI tooling to ensure we're using the best tools efficiently, pilot new tools, and flag when something needs to be updated or replaced

Ideally you’d have:

• 4+ years in web management, digital operations, or a related field, including direct people management
• Technical fluency: You’re comfortable in conversations about architecture, deployment pipelines, or front-end frameworks, even if you're not writing the code
• Experience managing AI integrations or APIs: genuine curiosity about how the underlying models work
• Operational instinct: you keep clean documentation, run tight sprint cycles, and treat QA as a feature, not a chore
• Calm under pressure: You're the person who steadies the team when something breaks
• Ambitious and meticulous: You’re motivated by achieving broader business results, and you sweat the small details that compound over time into a reputation for quality

AI is becoming vitally important in every function of our society. At Scale, our mission is to accelerate the development of AI applications. For 9 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 investment from Meta, we are doubling down on building out state of the art post-training algorithms to reach the performance necessary for complex agents in enterprises around the world. 

The Enterprise ML Research Lab works on the front lines of this AI revolution. We are working on an arsenal of proprietary research, tools, and resources that serve all of our enterprise clients. As a Staff Agent Post-Training MLRE, you will build out our next-gen Agent RL training platform. You’ll build out the platform that will train best-in-class Agents that achieve state of the art results on real enterprise use-cases. 

You’ll integrate cutting edge research into our training stack, enabling MLREs on the Enterprise AI team to deploy use-cases ranging from next-generation AI cybersecurity firewall LLMs to training foundation healthtech search models. If you are excited about shaping the future of the modern GenAI movement, we would love to hear from you!

You will: 

• Train state of the art models, developed both internally and from the community, to deploy to our enterprise customers. 
• Research cutting edge algorithms to integrate directly into our training stack.
• Design solutions that enable complex multi-agent systems to directly learn from both process + outcome based rewards.

Ideally you’d have:

• 5+ years of LLM training in a production environment
• Experience with post-training methods like RLHF/RLVR and related algorithms like PPO/GRPO etc.
• Publications in top conferences such as NEURIPS, ICLR, or ICML within the last two years
• PhD or Masters in Computer Science or a related field

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 adoption for Scale’s offering. 

We understand our customers’ needs and challenges and ensure that their voices are reflected in product development and messaging. We then partner closely with product, engineering, research, sales, comms,  and the broader marketing team to create a cohesive customer experience across all our channels. 

This role sits at the center of Scale’s GenAI data products, which power the world’s leading AI labs. As one of the largest providers of high-quality AI training data, we’ve built our reputation on speed, quality, frontier research, and a growing suite of multimodal data capabilities. 

The market is evolving fast, and we’re looking for a marketer who can go on offense to sharpen our narrative and build a playbook that earns the trust of the AI community. The ideal candidate combines strategic thinking with hands-on execution.

You will:

• Own positioning and messaging for Scale’s GenAI data products, articulating our differentiation on data quality, delivery speed, and multimodal breadth in a way that resonates with AI researchers and technical buyers.
• Lead the content and social strategy for Scale Labs’ dedicated online presence, taking a research-native approach that earns attention and credibility from the AI community.
• Build and maintain competitive intelligence and a sharp point of view on the data market, arming the team with differentiated positioning as the market evolves.
• Partner with Scale Labs researchers to amplify published work - leaderboards, benchmarks, and research papers - and translate it into pipeline and demand generation for the GenAI business
• Develop go-to-market strategies for new data offerings and modalities, working closely with product and sales to drive awareness and build market momentum.
• Collaborate cross-functionally with sales, engineering, and research to ensure consistent, compelling messaging across every customer touchpoint.

Ideally, you’d have:

• 5+ years of experience in product marketing, with a track record of marketing technical products to developer or research audiences.
• Strong technical fluency and passion for AI. You can hold a credible conversation about AI/ML fundamentals, training, and the role of data quality in model performance.
• Experience building social-native content and community strategies on platforms like X, with an instinct for what resonates with technical practitioners
• Excellent written communication and storytelling skills — you can make complex technical concepts compelling without oversimplifying them.
• Ability to work across functions and move fast in a dynamic, high-stakes environment.

Nice to haves:

• Familiarity with the AI training data market, or adjacent data and infrastructure spaces.
• An existing network or relationships within the AI research community.
• Experience navigating competitive markets where differentiation requires more than feature comparisons.

Scale is looking for a Compensation Manager to join our Total Rewards team. In this role, you'll help build and evolve our global compensation programs by providing analysis, insights, and modeling. We're seeking someone analytical, fast-paced, and excited about solving hard problems that impact our biggest investment - our people. You'll play a key role in designing and scaling our compensation processes as we continue to grow.

Responsibilities:

• Perform quantitative analyses to assist Leadership with key projects
• Conduct market benchmarking to determine pay targets and support business growth
• Contribute to the research, design, and delivery of compensation programs
• Support international expansion and M&A initiatives
• Collaborate with the Recruiting team on offer escalations and process optimization
• Develop and maintain tools to enhance efficiency of programs
• Build and integrate AI into Comp workflows
• Drive clarity, transparency, and understanding of compensation at Scale

Requirements:

• 6+ years experience on Compensation teams
• Experience with compensation programs, benchmarking, and market pricing. Experience with Radford and Pave is a plus.
• Ability to analyze large datasets and draw actionable insights
• Comfort working in a ultra fast paced environment
• Eagerness to build, learn, and grow

Nice to haves:

• Understanding of international compensation practices and regulatory environments
• Experience with pre-IPO equity programs
• Familiarity with AI tools (if not, we will teach you!)

We are seeking a highly technical Security Engineer to join our Product Security team. This role is integral to ensuring the security and integrity of our products and services. You will conduct in-depth code reviews, implement security best practices, and influence the overall security strategy. Your expertise in TypeScript, Python, AWS, CI/CD, SAST, DAST, and terraform orchestration will be crucial in identifying and mitigating potential security vulnerabilities. You will also structure complex problems, diagnose root causes independently, and clearly explain the mechanics and significance of security vulnerabilities, including their exploitability and potential impact.

You will:

• Leverage broad product security expertise to build and maintain software tooling that secures every layer of the modern AI/ML software ecosystem.
• Conduct in-depth code reviews to identify and remediate security vulnerabilities.
• Evaluate and enhance the security of our product offerings, through RFC and service review.
• Implement and maintain CI/CD pipelines with a strong focus on security.
• Perform Static Application Security Testing (SAST) and Dynamic Application Security Testing (DAST) to identify vulnerabilities in production code.
• Utilize terraform orchestration to ensure secure and efficient infrastructure management.
• Guide engineering teams to build robust long-term solutions that consider security and privacy. 
• Clearly explain the mechanics and significance of security vulnerabilities, including their exploitability and potential impact.
• Influence the security strategy and direction of the team, advocating for best practices and continuous improvement.

Ideally, you’d have:

• Demonstrated ability to drive multi-month security initiatives independently, from problem definition through execution, without requiring significant direction.
• Proven experience as a Security Engineer with a focus on product security.
• Proficiency in NodeJS, TypeScript, Python, and/or Kubernetes.
• Strong understanding of modern Javascript application design.
• Production experience operating and securing AWS infrastructure at scale.
• Hands-on experience with SAST and DAST tools and methodologies.
• Familiarity with terraform orchestration for infrastructure management.
• You can structure complex problems and diagnose root causes independently, providing actionable insights without requiring manager input.
• Excellent communication skills, with the ability to clearly present technical concepts and their implications to both technical and non-technical stakeholders.
• Demonstrated ability to influence security strategies and drive improvements within a team.
• Relevant security certifications (e.g., CISSP, CEH, OSCP) are a plus.

Scale's Finance Analytics and Data Science team is looking for an experienced data leader to manage a team of analysts and data engineers building internal tools and AI agents that automate workflows across finance and accounting.

In this role, you will lead a small team while staying technically hands-on, working closely with stakeholders across business finance, corporate finance, and accounting to understand their workflows and build systems that enable faster turnaround times with higher degrees of accuracy.

You will guide your team in designing data models, prototyping internal tools, and implementing agent-driven workflows using our internal data infrastructure, system integration tooling, Scale's proprietary AI platform, and emerging AI tools.

We're looking for someone who enjoys solving complex problems, building systems from the ground up, translating ambiguous business needs into scalable technical solutions, and developing the people around them.

Key Responsibilities

• Lead and grow a small team of analysts and engineers, providing technical mentorship, career development, and day-to-day guidance
  
  
• Design and develop end-to-end agent-driven workflows that automate finance and accounting processes, and improve operational efficiency
  
  
• Build scalable data models and pipelines that serve as the foundation for analytics assets (e.g., dashboards), agentic workflows and system automations
  
  
• Partner with stakeholders across finance, accounting, and customer operations to translate business requirements into technical requirements and system designs
  
  
• Collaborate with engineering teams in the development of internal tools to improve Scale’s financial system infrastructure
  
  
• Evangelize and support the adoption of AI-enabled automation across finance and accounting teams

Ideally, you have:

• 6+ years of experience in data analytics, analytics engineering, or data science role
  
  
• 1-3+ years of people management experience
  
  
• Expert knowledge of SQL and Python for data analysis and modeling
  
  
• Experience building internal tools, automation systems, or data products
  
  
• Experience building a reliable transformation layer and pipelines from ambiguous business processes using tools such DBT to create a foundational data models
  
  
• Experience partnering with engineering, and business stakeholders to automate manual workflows
  
  
• Strong problem-solving skills and the ability to operate independently in a fast-paced environment
  
  
• Excellent communication skills and experience working cross-functionally with business stakeholders
  
  
• Familiarity with finance or accounting terminology
  
  
• Experience with BI tools such as Tableau, Metabase, or Looker
  
  
• Familiarity with JavaScript and modern automation tooling is a plus but not required

About the Role

The Head of Financial Systems will own the strategy, implementation, and continuous improvement of Scale AI's finance technology stack. You are a builder-first leader who blends enterprise architecture with AI automation - eliminating manual workflows, tightening the financial data fabric, and enabling the Finance team to move with the speed and rigor the business demands. You will be the primary technology partner to the Finance leadership team, and the person ultimately accountable for the reliability, scalability, and intelligence of every system that touches the financial close, revenue, and spend lifecycle.

Key Responsibilities

ERP Ownership & Optimization Own the full lifecycle of our ERP environment (NetSuite or equivalent), including architecture, configuration, integrations, and roadmap. Ensure the platform reliably supports the General Ledger, AP, AR, Procure-to-Pay, Fixed Assets, Revenue Recognition, Sales Audit, and International Consolidations & Reporting.

Order-to-Cash & Procure-to-Pay Drive end-to-end process excellence across Order-to-Cash (Sales/Revenue Capture, Sales Audit, Billing) and Procure-to-Pay (Direct & Indirect Purchasing). Identify gaps between upstream systems and ERP, and close them through disciplined integration design.

AI Agent Deployment Identify opportunities to replace manual finance workflows with AI/LLM-powered agents. Build and manage internal agents that automate forecasting inputs, variance analysis, close task management, and reconciliation — reducing cycle time and surfacing actionable insights for Finance leadership.

Systems Integration & Data Architecture Design scalable data flows and APIs that connect the ERP to adjacent finance tools (billing, expense, FP&A, treasury) into a cohesive, auditable ecosystem. Ensure clean, governed data movement from source systems to the general ledger and reporting layer.

Operational Excellence & Controls Establish disciplined change management, clear data governance, and measurable SLAs across all financial systems. Stabilize environments to support audit readiness, SOX compliance, and regulatory requirements.Finance Stakeholder Partnership Serve as the primary technology partner to the CFO, Controller, FP&A, and Accounting teams. Translate complex technical constraints into business outcomes and align system roadmaps with Finance's strategic priorities.

Team Leadership Build and lead a high-impact Finance Systems team. Foster a culture of curiosity, speed, and user-centricity — where the team is as proud of a clean reconciliation workflow as any external product shipped.

What You'll Bring

• 8+ years of experience leading finance systems or enterprise application functions in a fast-paced, high-growth environment
• Deep, hands-on knowledge of ERP platforms (NetSuite strongly preferred) across core modules: GL, AP, AR, Fixed Assets, Revenue Recognition, Procure-to-Pay, Sales Audit, and International Consolidations
• Strong understanding of Order-to-Cash and Procure-to-Pay process design, including the touchpoints between upstream sales/procurement systems and the ERP
• Strong understanding of Sox IT General controls and track record implementing them
• Proven track record designing and deploying AI/LLM-powered workflows or agentic systems to improve Finance team efficiency
• Ability to design and govern scalable integrations and data flows across SaaS tools
• Experience influencing Finance leadership, translating technical complexity into clear business decisions
• Proficiency is an iPaaS platform (e.g., Workato, Mulesoft, Boomi, etc.) - Workato Certification is big plus
• Proficiency in Python or SQL to personally prototype, audit, and quality-check automation logic
• Familiarity with adjacent Finance tooling: expense management, FP&A platforms, billing systems, and treasury tools

Scale works with the industry’s leading AI labs to provide high quality data and accelerate progress in GenAI research. We are looking for Research Scientists and Research Engineers with expertise in LLM post-training (SFT, RLHF, reward modeling). This role will focus on optimizing data curation and eval to enhance LLM capabilities in both text and multimodal modalities.

In this role, you will develop novel methods to improve the alignment and generalization of large-scale generative models. You will collaborate with researchers and engineers to define best practices in data-driven AI development. You will also partner with top foundation model labs to provide both technical and strategic input on the development of the next generation of generative AI models.

You will:

• Research and develop novel post-training techniques, including SFT, RLHF, and reward modeling, to enhance LLM core capabilities in both text and multimodal modalities.
• Design and experiment new approaches to preference optimization.
• Analyze model behavior, identify weaknesses, and propose solutions for bias mitigation and model robustness.
• Publish research findings in top-tier AI conferences.

Ideally you’d have:

• Ph.D. or Master's degree in Computer Science, Machine Learning, AI, or a related field.
• Deep understanding of deep learning, reinforcement learning, and large-scale model fine-tuning.
• Experience with post-training techniques such as RLHF, preference modeling, or instruction tuning.
• Excellent written and verbal communication skills

• Published research in areas of machine learning at major conferences (NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR, etc.) and/or journals
• Previous experience in a customer facing role.

AI is becoming vitally important in every function of our society. At Scale, 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 usage of frontier data and models by building complex agents for enterprises around the world through our Scale Generative Platform (SGP).

The SGP ML team works on the front lines of this AI revolution. We interface directly with clients to build cutting edge products using the arsenal of proprietary research and resources developed at Scale. As an Applied AI Engineer, you’ll work with clients to create ML solutions to satisfy their business needs. Your work will range from building next-generation AI cybersecurity firewalls to creating transformative AI experiences in journalism to applying foundation genomic models making predictions about life-saving drug proteins. Daily data-driven experiments will provide key insights around model strengths and inefficiencies which you’ll use to improve your product’s performance. If you are excited about shaping the future of the modern AI movement, we would love to hear from you!

You will:

• Own, plan, and optimize the AI behind our Enterprise customer’s deepest technical problems
• Leverage SGP to build the most advanced AI agents across the industry including multimodal functionality, tool-calling, and more
• Have experience gathering business requirements and translating them into technical solutions 
• Meet regularly with customer teams onsite and virtually, collaborating cross-functionally with all teams responsible for their data and ML needs
• Push production code in multiple development environments, writing and debugging code directly in both our customer’s and Scale’s codebases.
• Be able and willing to multi-task and learn new technologies quickly

Ideally you'd have:

• 7+ years of full-time engineering experience, post-graduation
• A love for solving deeply complex technical problems with ambiguity using state of the art research and AI to accomplish your client’s business goals
• Strong engineering background: a Bachelor’s degree in Computer Science, Mathematics, or another quantitative field or equivalent strong engineering background.
• Deep familiarity with a data-driven approach when iterating on machine learning models and how changes in datasets can influence model results
• Experience working with cloud technology stack (eg. AWS or GCP) and developing machine learning models in a cloud environment
• Proficiency in Python to write, test and debug code using common libraries (ie numpy, pandas)

Nice to haves:

• Strong knowledge of software engineering best practices
• Have built applications taking advantage of Generative AI in real, production use cases
• Familiarity with state of the art LLMs and their strengths/weaknesses

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, fueling the most exciting advancements in AI, including generative AI, defense applications, and autonomous vehicles. With our recent Series F round, we’re amplifying access to high-quality data to drive progress toward Artificial General Intelligence (AGI). Building on our history of model evaluation with enterprise and government customers, we are expanding our capabilities to set new standards for both public and private evaluations.

About This Role

This role operates at the forefront of AI research and real-world implementation, with a strong focus on reasoning within large language models (LLMs). The ideal candidate will study the data types critical for advancing LLM-based agents, including browser and software engineering (SWE) agents. You will play a key role in shaping Scale’s data strategy by identifying the most effective data sources and methodologies for improving LLM reasoning. Success in this role requires a deep understanding of LLMs, planning algorithms, and novel approaches to agentic reasoning, as well as creativity in tackling challenges related to data generation, model interaction, and evaluation. You will contribute to impactful research on language model reasoning, collaborate with external researchers, and work closely with engineering teams to bring state-of-the-art advancements into scalable, real-world solutions.

Ideally, you’d have:

• Practical experience working with LLMs, with proficiency in frameworks like PyTorch, JAX, or TensorFlow. You should also be skilled at rapidly interpreting research literature and turning new ideas into working prototypes.

• A track record of published research in top ML and NLP venues (e.g., ACL, EMNLP, NAACL, NeurIPS, ICML, ICLR, CoLLM, etc.).

• At least three years of experience solving complex ML challenges, either in a research setting or product development, particularly in areas related to LLM capabilities and reasoning.

• Strong written and verbal communication skills, along with the ability to work effectively across teams.

Nice to have:

• Hands-on experience fine-tuning open-source LLMs or leading bespoke LLM fine-tuning projects using PyTorch/JAX.

• Research and practical experience in building applications and evaluations related to LLM-based agents, including tool-use, text-to-SQL, browser agents, coding agents, and GUI agents.

• Experience with agent frameworks such as OpenHands, Swarm, LangGraph, or similar.

• Familiarity with advanced agentic reasoning techniques such as STaR and PLANSEARCH.

• Proficiency in cloud-based ML development, with experience in AWS or GCP environments.

Our research interviews are designed to assess candidates' ability to prototype and debug ML models, their depth of understanding in research concepts, and their alignment with our organizational culture. We do not conduct LeetCode-style problem-solving assessments.

Scale's Physical AI business unit is dedicated to solving the data bottleneck across Robotics, Autonomous Vehicles, and Computer Vision. This position will be a key contributor in conducting applied research in Physical AI and developing ML pipelines for processing, training, and fine-tuning on data collected by Scale, with a specific focus on optimizing algorithms and pipelines to run efficiently on GPUs in the cloud. In this role, you will have the opportunity to advance research, shape Scale’s offerings, and expand the frontier of data and model evaluation for Physical AI.

The Role 

As an ML Systems Engineer on the Physical AI team, you will design and build platforms for scalable, reliable, and efficient serving of foundation models specifically tailored for physical agents. Our platform powers cutting-edge research and production systems, supporting both internal research discovery and external customer use cases for autonomous vehicles and robotics.

The ideal candidate combines strong ML fundamentals with deep expertise in backend system design. You’ll work in a highly collaborative environment, bridging the gap between Physical AI research and production engineering to accelerate innovation across the company.

You Will: 

• Build & Scale: Maintain fault-tolerant, high-performance systems for serving robotics-related models and foundation models at scale, ensuring low latency for real-time applications.
• Platform Development: Build an internal platform to empower model capability discovery, enabling faster iteration cycles for research teams working on robotics.
• Collaborate: Work closely with Robotics researchers and Computer Vision engineers to integrate and optimize models for production and research environments.
• Design Excellence: Conduct architecture and design reviews to uphold best practices in system scalability, reliability, and security.
• Observability: Develop monitoring and observability solutions to ensure system health and real-time performance tracking of model inference.
• Lead: Own projects end-to-end, from requirements gathering to implementation, in a fast-paced, cross-functional environment.

Ideally, You’d Have: 

• Experience: 4+ years of experience building large-scale, high-performance backend systems, with deep experience in machine learning infrastructure.
• Algorithm Optimization: Deep experience optimizing computer vision and other machine learning algorithms for cloud environments, including GPU-level algorithm optimizations (e.g., CUDA, kernel tuning).
• Programming: Strong skills in one or more systems-level languages (e.g., Python, Go, Rust, C++).
• Systems Fundamentals: Deep understanding of serving and routing fundamentals (e.g., rate limiting, load balancing, compute budgets, concurrency) for data-intensive applications.
• Infrastructure: Experience with containers (Docker), orchestration (Kubernetes), and cloud providers (AWS/GCP).
• IaC: Familiarity with infrastructure as code (e.g., Terraform).
• Mindset: Proven ability to solve complex problems and work independently in fast-moving environments.

Nice to Haves: 

• Exposure to Vision-Language-Action (VLA) models.
• Knowledge of high-performance video processing (e.g., FFmpeg, NVDEC/NVENC) or 3D data handling (point clouds).
• Familiarity with robotics middleware (e.g., ROS/ROS2) or AV data formats.

Scale AI is the data engine for the entire AI industry. Our mission is to accelerate the development of AI applications by providing organizations with the high-quality data they need. The Physical AI team at Scale is focused on the next frontier: building general AI that can reason and act in the physical world. By leveraging Scale’s massive data infrastructure, we are helping frontier labs build Foundation Models for Physical AI that will redefine the future of automation.

Role Overview

As the Technical Lead Manager (TLM) for the Physical AI team of Scale, you will bridge the gap between cutting-edge Machine Learning research and physical robot deployment. You will lead a high-performing team of Research Engineers while remaining a hands-on technical contributor (~60% of your time).

Your primary focus will be the development and evaluation of Large-Scale Foundation Models (e.g VLAs, World models) that allow robots and AVs to generalize across diverse tasks, environments, and morphologies.

Key Responsibilities

Technical Leadership & Research

• Model Scaling: Direct research into scaling laws for Physical AI, determining how to best utilize massive datasets for pre-training and fine-tuning generalist policies.
• VLA and World model development: Develop novel methods for developing and evaluating models, including new Physical AI industry benchmarks
• Hands-on Modeling: Actively write code to implement, train and test SOTA architectures. Conduct research on Physical AI data collection, cross-embodiment training, and policy fine-tuning.  
• Data Strategy: Collaborate with internal labeling teams to design "robotic-native" data pipelines, including the use of VLMs for automated trajectory annotation and data synthesis.
• Collaborate closely with customers to drive the industry forward in using Scale data

Team Management & Execution

• Mentorship: Lead and grow a team of 4-6 elite Physical AI  researchers, fostering a culture of high-velocity experimentation and rigorous evaluation.
• Paper-to-Product: Translate the latest research from NeurIPS, ICRA, and CVPR into production-ready features for Scale’s Physical AI partners.
• Cross-functional Alignment: Work with cross-functional teams (e.g Product and Operations) to bring our research breakthroughs into production. 

Required Qualifications

AI/ML Excellence

• Deep Learning Mastery: Expert-level proficiency in PyTorch, with deep knowledge of Transformer architectures, Attention mechanisms, and Self-Supervised Learning.
• VLM/VLA Experience: Proven track record of working with Vision-Language Models (e.g., CLIP, PaLM-E) and adapting them for spatial reasoning or embodied tasks.
• Generative AI: Experience with Diffusion Models for sequence generation or Generative World Models for predictive modeling.

Physical AI & Software Background

• Embodied AI: Strong understanding of Physical AI stack, including imitation learning, reinforcement learning (RL), and multi-modal sensor fusion.
• Infrastructure: Experience with large-scale distributed training across GPU clusters and high-performance data loading.
• Leadership: 1+ years of experience leading technical teams or projects in a research-intensive environment.

Nice to Haves:

• Publication Record: First-author publications at top-tier AI/ML conferences (NeurIPS, CVPR, ICRA, CoRL).
• Hardware Generalization: Experience building models that work across different robot types (arms, mobile bases, humanoids).
• Sim-to-Real: Experience with high-fidelity simulators (e.g., Isaac Gym, MuJoCo) and the nuances of physical domain adaptation.

As the leading data and evaluation partner for frontier AI companies, Scale is dedicated to advancing the evaluation and benchmarking of large language models (LLMs). We are building industry-leading LLM evals, setting new standards for model performance assessment. Our mission is to develop rigorous, scalable, and fair evaluation methodologies to drive the next generation of AI capabilities.

Our Research teams work with the industry’s leading AI labs to provide high quality data and accelerate progress in GenAI research. As a Staff Machine Learning Research Scientist on the LLM Evals team, you will lead the development of novel evaluation methodologies, metrics, and benchmarks to measure the capabilities and limitations of frontier LLMs. You will help define what "good" looks like in generative AI, driving research that informs both our internal roadmap and the broader research community. This role is critical for designing and executing a roadmap that defines best practices in data driven AI development and will accelerate the next generation of generative AI models in partnership with top foundational model labs.

You will:

• Drive research on the effectiveness and limitations of existing LLM evaluation techniques.
• Design and develop novel evaluation benchmarks for large language models, covering areas such as instruction following, factuality, robustness, and fairness. 
• Communicate, collaborate, and build relationships with clients and peer teams to facilitate cross-functional projects.
• Collaborate with internal teams and external partners to refine metrics and create standardized evaluation protocols.
• Implement scalable and reproducible evaluation pipelines using modern ML frameworks.
• Publish research findings in top-tier AI conferences and contribute to open-source benchmarking initiatives.
• Mentor and guide research scientists and engineers, providing technical leadership across cross-functional projects.
• Stay deeply engaged with the ML research community, tracking emerging work and contributing to the advancement of LLM evaluation science.
• Thrive in a high-energy, fast-paced startup environment and are ready to dedicate the time and effort needed to drive impactful results.

Ideally you'd have:

• 5+ years of hands-on experience in large language model, NLP, and Transformer modeling, in the setting of both research and engineering development
• Experience and track of recording in landing major research impacts in a fast-paced environment
• Experience tech leading a team of research scientists and research engineers
• Excellent written and verbal communication skills
• Published research in areas of machine learning at major conferences (NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR, etc.) and/or journals
• Previous experience in a customer facing role.

AI is becoming vitally important in every function of our society. At Scale, our mission is to accelerate the development of AI applications. For 9 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 investment from Meta, we are doubling down on building out state of the art post-training algorithms to reach the performance necessary for complex agents in enterprises around the world. 

The Enterprise ML Research Lab works on the front lines of this AI revolution. We are working on an arsenal of proprietary research and resources that serve all of our enterprise clients. As an ML Sys Research Engineer, you’ll work on building out the algorithms for our next-gen Agent RL training platform, support large scale training, and research and integrate state-of-the-art technologies to optimize our ML system. Your customer will be other MLREs and AAIs on the Enterprise AI team who are taking the training algorithms and applying them to client use-cases ranging from next-generation AI cybersecurity firewall LLMs to training foundation healthtech search models. If you are excited about shaping the future of the modern AI movement, we would love to hear from you!

You will: 

• Build, profile and optimize our training and inference framework.
• Post-train state of the art models, developed both internally and from the community, to define stable post-training recipes for our enterprise engagements. 
• Collaborate with ML teams to accelerate their research and development, and enable them to develop the next generation of models and data curation..
• Create a next-gen agent training algorithm for multi-agent/multi-tool rollouts.

Ideally you’d have:

• At least 1-3 years of LLM training in a production environment
• Passionate about system optimization
• Experience with post-training methods like RLHF/RLVR and related algorithms like PPO/GRPO etc.
• Ability to demonstrate know-how on how to operate the architecture of the modern GPU cluster
• Experience with multi-node LLM training and inference
• 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.
• PhD or Masters in Computer Science or a related field

Come join our legal team to work on the most exciting legal, policy, and operational issues at the leading edge of AI. We're seeking strong product lawyers with specialized expertise in intellectual property law. As product counsel, you will advise on all legal aspects of product development, launch, and operations - including regulatory compliance, user terms, and risk management - while bringing deep expertise in your specialized legal area.

The ideal candidate will have deep subject matter expertise in intellectual property law, a technology background, and a demonstrable history of providing practical product counsel to solve complex, time-sensitive problems in close partnership with cross-functional teams. This role reoprts to the Associate General Counsel, IP & Product.

You will:

• Strategic Product Advice: Lead IP strategy for product development, embedding IP protection into the full product lifecycle from conception to commercialization, while also advising on related product and regulatory matters in collaboration with the broader legal team.
• Cross-Functional Collaboration: Partner with Research, Product, Engineering, Operations, Communications, and Marketing teams to mitigate IP risks in product development, data licensing, and open-source governance.
• IP Counsel: Support management of Scale's worldwide IP portfolio including patents and trademarks; assist with patent prosecution and trademark registration and enforcement.
• Risk Mitigation: Advise on third-party, synthetic, and open-source data and models, ensuring compliance with licensing requirements; design open-source governance policies.
• Agreements: Support drafting and negotiation of commercial agreement provisions involving intellectual property.
• Specialized Expertise: Provide counsel on machine learning, robotics, and other technical areas, with ability to engage effectively with technical teams on complex engineering and product issues.
• Training: Develop and deliver IP and data licensing training to enhance Scale's compliance culture.

Ideally you'd have:

• Experience: 5+ years of experience in intellectual property law at a top-tier law firm and/or in-house legal department (ideally product counseling within a high-growth technology company). Experience advising on broader product or regulatory matters is a plus.
• Education: JD and active membership in at least one U.S. state bar (California preferred) in good standing.
• Strategic Thinking: Ability to think strategically at a high level and from deep in the details to drive complex problem-solving and develop creative, business-forward solutions.
• Risk Calibration: Ability to calibrate risk, distinguish business from legal risk, and communicate it clearly to executive, business, and technical audiences.
• Collaboration: Roll-up-your-sleeves attitude to tackle projects large and small with a low-ego, collaborative approach across the organization.
• Agility and Organization: Ability to think quickly in a fast-paced environment with excellent organizational and communication skills.
• Technical Fluency: Deep interest in artificial intelligence, generative AI, and machine learning technology, with the ability to engage effectively with technical teams.

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 users are your neighbors) to identify bottlenecks and ship fast, pragmatic solutions
• Own core systems critical to our contributor platform, with direct impact on Scale’s GenAI data pipeline and business outcomes
• Architect and scale infrastructure capable of handling millions of tasks per week with high reliability and low latency
• Partner cross-functionally with ML teams, Forward Deployed Engineers, and Product to ensure data quality and operational excellence
• Contribute to a strong engineering culture while setting best practices for teammates through mentorship, code reviews, and process improvements

Requirements:

• 5+ years of software engineering experience, ideally in high-growth, product-focused environments
• Proven track record of shipping production systems at scale
• Drive reliability and performance across critical infrastructure systems, ensuring our platforms scale predictably and operate with high availability.
• Strong technical depth in one or more areas: front-end frameworks, distributed systems, data infrastructure, or developer tooling
• Experience working across the stack, ideally with React, TypeScript, Node.js, Python, MongoDB, Elasticsearch, and/or Temporal
• Strong product sense and ability to translate ambiguous problems into technical solutions
• Comfortable working in a fast-paced, high-ownership environment with a bias toward execution
• Excited to join a dynamic hybrid team based in San Francisco or New York City

As the leading data and evaluation partner for frontier AI companies, Scale is dedicated to advancing the evaluation and benchmarking of large language models (LLMs). We are building industry-leading LLM evals, setting new standards for model performance assessment. Our mission is to develop rigorous, scalable, and fair evaluation methodologies to drive the next generation of AI capabilities.

Our Research teams work with the industry’s leading AI labs to provide high quality data and accelerate progress in GenAI research. As the Tech Lead Manager of the LLM Evals Research team, you will lead a talented team of research scientists and research engineers focused on developing and implementing novel evaluation methodologies, metrics, and benchmarks to assess the capabilities and limitations of our cutting-edge LLMs. This role is critical for designing and executing a roadmap that defines best practices in data driven AI development and will accelerate the next generation of generative AI models in partnership with top foundational model labs. 

You will:

• Lead a team of highly effective research scientists and research engineers on LLM evals.
• Conduct research on the effectiveness and limitations of existing LLM evaluation techniques.
• Design and develop novel evaluation benchmarks for large language models, covering areas such as instruction following, factuality, robustness, and fairness. 
• Communicate, collaborate, and build relationships with clients and peer teams to facilitate cross-functional projects.
• Collaborate with internal teams and external partners to refine metrics and create standardized evaluation protocols.
• Implement scalable and reproducible evaluation pipelines using modern ML frameworks.
• Publish research findings in top-tier AI conferences and contribute to open-source benchmarking initiatives.
• Remain up-to-date on ongoing research in the team, help work through technical challenges, and be involved in design decisions
• Remain deeply involved in the research community, both understanding trends, and setting them
• Thrive in a high-energy, fast-paced startup environment and are ready to dedicate the time and effort needed to drive impactful results.

Ideally you'd have:

• 5+ years of hands-on experience in large language model, NLP, and Transformer modeling, in the setting of both research and engineering development
• Experience and track of recording in landing major research impacts in a fast-paced environment
• Experience supporting and leading a team of research scientists and research engineers
• Excellent written and verbal communication skills
• Published research in areas of machine learning at major conferences (NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR, etc.) and/or journals
• Previous experience in a customer facing role.

At Scale, we believe that AI will dramatically improve the world, and our mission is to develop reliable AI systems for the world's most important decisions. To help achieve this mission, we are looking for an HR Business Partner to partner with our Gen AI Operations team. 

Scale AI's 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 they produced is described as some of the most important work for how humanity will interact with AI. 

As the HR Business Partner, Operations, you will be deeply embedded within the Gen AI Operations team, advise team members as our business scales, and will support leaders in all people-related matters. You will collaborate closely with cross-functional teams such as HR Operations, Recruiting, Finance, Legal, and IT to make the Operations team as successful as possible.  

You will:

• Provide end-to-end HRBP support across our growing and evolving Gen AI business unit, including directly driving org health initiatives, influencing org structure to effectively scale the team, and developing and implementing creative solutions as the team navigates new markets.  
• Establish yourself as a trusted advisor and a knowledgeable, reliable, and empathetic partner for our employees and leaders across the Enterprise team
• Coach and advise leaders on best people practices and uplevel manager skill sets 
• Lead project management for all people programs for the Enterprise organization, including org planning, onboarding, performance cycles, engagement surveys, and career development efforts
• Drive organization and order for people data and use it to provide insights and recommendations to leaders
• Work in a hybrid work environment (3 days/week) at our San Francisco Headquarters or New York office 

Ideally you'd have:

• 5+ years of experience working in HR with progression and growth in scope, with 3+ years of experience in an HR Business Partner role at a fast-paced, high-growth company 
• Demonstrated experience engaging with executive-level leadership on org-wide initiatives, and ability to partner and build relationships with senior leadership 
• Strong ability to relate to, empathize with, and quickly build trust with people from diverse backgrounds
• Proven ability to thrive in a fast-paced, iterative environment and embrace changes in focus and direction as needed
• A passion for building scalable processes in a creative, thoughtful, and organized way 
• Experience supporting a global workforce across various job functions

Nice to haves:

• Strong knowledge of Google Sheets/Excel and demonstrated ability to influence decisions with data.
• Experience in Consulting or in an Operations and Strategy role at a fast-paced company.

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 developing and deploying applications in a cloud-native environment. Understanding of containerization (e.g., Docker) and container orchestration (e.g., Kubernetes) is a plus
• Data Engineering: Knowledge of ETL (Extract, Transform, Load) processes and experience in building data pipelines to integrate and process diverse data sources. Understanding of data modeling, data warehousing, and data governance principles
• AI Application Integration: Familiarity with integrating Large Language Models (LLMs) and building agentic workflows. Understanding of prompt engineering, retrieval-augmented generation (RAG), and agent orchestration is beneficial.
• Problem Solving: Strong analytical and problem-solving skills to understand complex challenges and devise effective solutions. Ability to think critically, identify root causes, and propose innovative approaches to overcome technical obstacles
• Collaboration and Communication: Excellent interpersonal and communication skills to effectively collaborate with cross-functional teams, stakeholders, and customers. Ability to clearly articulate technical concepts to non-technical audiences and foster a collaborative work environment
• Adaptability and Learning Agility: Willingness to embrace new technologies, learn new skills, and adapt to defining and evolving project requirements. Ability to quickly grasp and apply new concepts and stay up-to-date with emerging trends in software engineering