#TeamNextdoor

Nextdoor (NYSE: NXDR) is the essential neighborhood network. Neighbors, public agencies, and businesses use Nextdoor to connect around local information that matters in more than 350,000 neighborhoods across 11 countries. Nextdoor builds innovative technology to foster local community, share important news, and create neighborhood connections at scale. Download the app and join the neighborhood at nextdoor.com.

Meet Your Future Neighbors

As an iOS Software Engineer at Nextdoor, you’ll join a focused team of Developers, Product Managers, and Designers who are passionate about using technology to cultivate a kinder world where everyone has a neighbor they can rely on. We are a small team of mobile engineers that work on app infrastructure and features to deliver our values to our members. We care about moving fast and delivering impact, without compromising on quality and reliability.

At Nextdoor, we offer a warm and inclusive work environment that embraces a hybrid employment model, blending an in office presence and work from home experience for our valued employees. 

The Impact You’ll Make

We believe in empowering our teams to own all aspects of bringing Nextdoor to life. As such, you’ll get the opportunity to make key contributions across our iOS stack - this includes developing and improving our networking, analytics, experiments, and modular app structure, in addition to making direct contributions to your team’s product area.

Beyond day-to-day technical work, you’ll also get the chance to collaborate with product managers and designers to drive Nextdoor forward. We believe engineers should have a stake over all aspects of the product - from coming up with the next big ideas to build, through helping set expectations and plan roadmaps, all the way through understanding the impact of new features through rigorous data analysis. As your career at Nextdoor develops, you’ll also get the chance to mentor other team members and grow your role towards what you’re most passionate about.

• Participate in in-person Nextdoor events such as trainings, off-sites, volunteer days, and team building exercises
• Build in-person relationships with team members and contribute to Nextdoor’s company culture

What You’ll Bring to The Team

• 3+ Years of experience in a mobile development role with a proven track record shipping and owning non-trivial iOS features in production. 
• Expertise in Swift and Xcode IDE including the build system
• Robust knowledge of iOS development ecosystem, including core system libraries
• Proven experience building complex, high-quality iOS applications, and strong knowledge of iOS app design principles, architectural patterns, testing, and best practices
• Ability to communicate technical tradeoffs clearly in writing (design docs, PR reviews, etc.) and verbally (cross-functional syncs)
• Strong motivation to continuously learn and share knowledge about new technologies and systems.
• Demonstrated ability to thrive in a fast-paced environment, prioritizing high-impact work and adapting strategies in real time.
• Thoughtful use of AI tooling in day-to-day engineering - knows when it helps and when it gets in the way.

Bonus Points

• Experience writing automated tests for iOS applications
• Experience with accessibility features on iOS

Rewards

Compensation, benefits, perks, and recognition programs at Nextdoor come together to create our total rewards package. Compensation will vary depending on your relevant skills, experience, and qualifications. Compensation may also vary by geography.

The starting salary for this role is expected to range from $142,000 - $250,000 on an annualized basis, or potentially greater in the event that your 'level' of proficiency exceeds the level expected for the role.

We expect to award a meaningful equity grant for this role. With quarterly vesting, your first vest date will take place within 3 months of your start date.

When it comes to benefits, we have you covered! Nextdoor employees can choose between a variety of health plans, including a 100% covered employee only plan option, and we also provide a OneMedical membership for concierge care.

At Nextdoor, we empower our employees to build stronger local communities. To create a platform where all feel welcome, we want our workforce to reflect the diversity of the neighbors we serve. We encourage everyone interested in our mission to apply. We do not discriminate on the basis of race, gender, religion, sexual orientation, age, or any other trait that unfairly targets a group of people. In accordance with the San Francisco Fair Chance Ordinance, we always consider qualified applicants with arrest and conviction records.

For information about our collection and use of applicants’ personal information, please see Nextdoor's Personnel Privacy Notice, found here.

About your role

You’ll bring to the role a passion for delivering a seamless and engaging employee experience through operational excellence. The ideal candidate is a detail-oriented and tech-savvy HR professional with hands-on HRIS experience and a strong understanding of core HR processes. In this role, you will support key People Operations programs across the employee lifecycle, ensuring accuracy, compliance, and continuous process improvement.

How you will make a difference day to day

• Manage HRIS transactions throughout the employee lifecycle, including onboarding, job changes, promotions, compensation updates, and offboarding

• Support the administration of company benefits programs, including new hire enrollment and qualifying life event changes

• Ensure new hires are enrolled in required training plans; support rollout, tracking, and reporting of annual compliance training

• Support and help drive People Operations initiatives and cross-functional projects, including process improvements and system enhancements

• Assist in administering performance review cycles, including assessment kick-off, progress monitoring, and completion reporting

• Monitor the HR email inbox and Slack channels to provide timely and accurate responses to employee inquiries

• Develop proficiency and become a subject-matter expert in HR systems, processes, and communication platforms

• Help ensure adherence to established HR policies, procedures, and best practices

• Support payroll processing by verifying data accuracy and compliance with internal requirements

• Maintain and update process documentation and refresh HR content on the company Intranet

• Utilize Google Workspace tools (Gmail, Calendar, Docs, Slides, and basic Sheets) to support daily operations and reporting

What you´ll need

• 3–5 years of HR Operations experience with hands-on HRIS work

• Experience working for a tech company, with the ability to thrive in a fast-paced environment and effectively manage competing priorities

• Experience supporting a range of People Operations projects and initiatives

• Strong organizational skills with sharp attention to detail

• Service-oriented mindset with strong written and verbal communication skills

• Ability to manage sensitive information with discretion and professionalism

• Exposure to HRIS configuration, implementation, or system integrations a plus

Not sure if you meet all the qualifications? Apply anyway! We value diverse experiences and encourage you to bring your unique talents to our team!

Benefits & Perks

• Comprehensive health plans (including Medical, Dental, and Vision insurance for full-time employees)
• Unlimited PTO
• Competitive salary packages
• Life insurance
• Disability benefits
• Supplemental Optional Life Insurance Benefits
• FSA Options Optional
• HSA with Company Match
• 401k program with Company Match
• Wellhub & ClassPass fitness platforms
• Comprehensive Pet Insurance options
• Financial Wellbeing & Student Loan Program access
• Access to additional Mental Health & Wellbeing resources
• Pre-tax Commuter/Transit Benefits
• Free Rocket Lawyer account with online access to an extensive legal documents library and brilliant licensed attorneys at discounted rates 

Interview Process

• Recruiter Phone Screen
• Role Assessment(s)
• Hiring Manager Interview
• Panel Interviews
• Final Interview

Our Integrated Marketing team partners closely with product, product marketing, SEO/AEO, CMS, lifecycle marketing, paid media, and web publishing to bring our brand and campaigns to life across every customer touchpoint.

As we expand our search visibility, organic social presence, and cross-channel campaign execution, we are investing in thoughtful, research-backed messaging that supports acquisition, engagement, and brand authority in the legal tech space.

About your role

• As a Content & Social Marketing Intern, you’ll support high-volume copy production across lifecycle marketing, paid media, website/AEO updates, and organic social channels. This is an early-career opportunity ideal for someone building foundational skills in copywriting, content strategy, and social marketing within a fast-paced SaaS environment.
• You’ll collaborate closely with marketing managers, designers, and video partners to adapt messaging across formats, support social listening efforts, and contribute to research-backed content. You’ll gain hands-on experience translating brand voice into multi-channel marketing assets that support growth and visibility.

How you will make a difference day to day

Support Cross-Channel Copy Execution

• Create and adapt campaign messaging across email, paid media, social, and website formats.
• Draft copy for recurring marketing initiatives, seasonal moments, and GTM launches.
• Ensure consistency in brand voice across channels and asset types.
• Update situation-based landing pages as new guidelines and formats are established.

Support Organic Social & Community Engagement

• Assist with social listening and trend monitoring to identify timely content opportunities.
• Draft responses and engage in comments across social platforms.
• Research competitors and industry conversations to inform positioning.
• Contribute ideas for social series or content pilots aligned with growth goals.

Research & Operational Support

• Conduct research for positioning claims, survey data, and performance-backed messaging.
• Organize shared documents, content libraries, and workflow trackers.
• Document recurring marketing processes and content guidelines.

Cross-Functional Collaboration & Growth

• Collaborate with the design, social, web publishing, and SEO/AEO teams to understand campaign goals and channel requirements.
• Participate in creative reviews and feedback sessions.
• Learn how messaging supports SEO/AEO, paid performance, and organic growth strategies.
• Develop foundational skills in brand storytelling, performance marketing, and content optimization.

What you’ll need

• Currently pursuing or recently completed a degree in Marketing, Communications, Journalism, Social Media, or a related field.
• Strong written communication skills with attention to tone and clarity.
• Interest in copywriting, content strategy, and social media marketing.
• Ability to manage multiple small projects and meet deadlines.
• Comfort receiving feedback and iterating on written work.
• Curiosity about digital marketing, search visibility, and audience engagement.

A plus if you have 

• Basic understanding of social media platforms and other marketing channels like email, paid ads, etc. 
• Familiarity with tools such as Figma (for collaboration), Sprout Social, and Google Docs.
• Portfolio showcasing writing samples (academic, freelance, or personal projects).
• Interest in legal tech, SaaS, or educational content.

Interview Process

• Recruiter Phone Screen
• Role Assessment(s)
• Hiring Manager Interview
• Final Interview

About the job

BuildOps is looking for a Senior Procurement Manager to own our end-to-end vendor lifecycle, from intake and evaluation through negotiation, contracting, and ongoing optimization.This role will centralize how we buy software, infrastructure, and services, drive cost savings, enforce commercial guardrails, and free up teams to focus on building and selling. 

You will partner closely with Finance, Legal, IT/Security, and department leaders to ensure every dollar of spend is intentional, well negotiated, and aligned with our strategic priorities.

What you will do

Vendor strategy and intake: 

• Own the vendor intake process, ensuring new requests are aligned with budget, headcount plans, and existing tools.
• Evaluate whether an existing solution can meet the need before approving net new spend.
• Partner with budget owners to prioritize requests based on impact, risk, and ROI.

Sourcing, negotiation, and renewals: 

• Lead RFPs, pricing benchmarks, and competitive bids for key categories (for example SaaS, infrastructure, professional services).
• Negotiate commercial terms including price, ramp structure, auto renewal, caps on increases, and termination rights.
• Build and manage a renewal calendar, ensuring we engage vendors well ahead of renewal dates to avoid last minute compromises.
• Develop a point of view on AI and cloud provider spend management, including token-based consumption models, structuring commitments, monitoring usage, and negotiating guardrails to control cost as AI becomes a core infrastructure layer.

Contracting and guardrails: 

• Develop and maintain a procurement playbook that defines our standard commercial positions (for example no auto renewal by default, limits on term length, renewal caps, usage thresholds).
• Partner with Legal to streamline low risk and standard contracts by creating templates and fallback positions that reduce review time.
• Ensure deals comply with security, privacy, and data handling requirements in partnership with IT/Security.

Process and systems: 

• Own or co own the procurement workflow in Ramp (or equivalent), including approval thresholds, routing rules, and documentation standards.
• Ensure all vendor records, contracts, and key terms are accurately captured in our systems (for example Ramp, ERP, contract repository).
• Continuously simplify and automate procurement steps so stakeholders have a clear, fast path from request to signed contract.
• Identify and aggressively remediate Shadow IT and unsanctioned SaaS by partnering with IT/Security and Finance to surface off process spend, bring critical tools into the formal procurement workflow, and decommission redundant or non compliant tools.

Spend analytics and savings: 

• Build and maintain dashboards and reporting on vendor spend, category trends, and savings realized.
• Identify and execute on consolidation and rationalization opportunities (for example duplicate tools, underused licenses, overlapping vendors).
• Track and communicate savings targets and performance, including both hard savings and cost avoidance.

Stakeholder partnership: 

• Serve as the primary point of contact for vendor related questions and escalations across the company.
• Educate stakeholders on procurement best practices and how to engage early to get the best outcomes.
• Partner with Finance on budgeting and forecasting for vendor spend, including scenario analysis for major contracts.

What we look for

Must haves: 

• 5+ years of procurement, strategic sourcing, or vendor management experience, ideally in B2B SaaS or technology.
• Demonstrated track record of negotiating complex SaaS and infrastructure deals and delivering measurable savings.
• Strong understanding of commercial terms, including renewal structures, usage based pricing, SLAs, and basics of liability and indemnity.
• Comfortable working with Finance and Legal to align on budgets, risk tolerance, and contract standards.
• Highly analytical, able to model scenarios and quantify trade offs (for example TCO, payback, ROI, unit economics)
• Excellent communication and influence skills, able to push back constructively while maintaining strong relationships.
• Self starter who can build processes in an environment that is still scaling and maturing its procurement function.

Nice to have: 

• Experience implementing or owning workflows in Ramp, Coupa, Procurify, or similar tools.
• Background working with global vendors and multi-entity structures.
• Prior experience in a high growth startup environment.

Who you are

• You are a strategic, hands-on procurement leader who enjoys building structure in a scaling environment and acting as a trusted advisor to stakeholders.
• You are comfortable digging into details of contracts and pricing models while also stepping back to design processes, playbooks, and systems that make vendor management more efficient and transparent across the company.

Compensation

• LA/SF salary range: $165,000.00 - $185,000.00 base salary + annual bonus opportunity.

Scale plays a vital role in the development of AI applications. Our customer base is growing exponentially, and you will be on the front lines, ensuring that the world's most innovative companies become passionate, lifelong Scale customers.

Solutions Engineers partner closely with AEs, Product, and MLEs to lead prospective customers through pre-sales, delivering customized demos and pilots to secure the “technical win”. Solutions Engineers scope customer technical requirements and develop an actionable SOW. They will work closely with the delivery team to help with initial implementation. Solutions Engineers are relentlessly curious about customer needs and pain points. They employ their expert Scale product knowledge and GenAI knowledge to design solutions that best address these needs. Solutions Engineers are strong relationship builders, great project managers, and provide technical expertise.

You will:

• Partner with Scale AEs on the customer journey, delivering tailored demos and prototypes according to the customer's requirements.
• Develop technical domain expertise in Generative AI / large language model applications for Enterprise use cases, including customers in financial services, insurance, SaaS, and similar enterprises.
• Be accountable for securing the “technical win” by unblocking technical challenges
• Interact with customers daily to understand their needs and design solutions to better serve them.
• Design and develop “Scopes of Work” by breaking down customer challenges into a project plan
• Work closely with forward-deployed Software and Machine learning Engineers to develop agents in the initial post-sales stage
• Work with AEs and PMs to identify customer-specific feature requests.
• Drive strategic initiatives to improve the efficiency and effectiveness of the Solution Engineering team.

Ideally, you'd have:

• Strong engineering background with prior experience working with clients in a pre or post-sales capacity to realize business goals.
• Prior experience developing with Python, Java and/or other web development languages.
• Experience working in enterprise SaaS, cloud tech, finance, fintech or similar industries in a technical capacity with end-customer engagement.
• A track record as a self-starter, motivated to independently unblock technical issues in the field with the customer, away from the mothership.
• Presentation skills with a high degree of technical credibility when speaking with executives and front-line engineers.
• High level of comfort communicating effectively across internal and external organizations.
• Intellectual curiosity, empathy, and ability to operate with high velocity.

Nice to haves:

• GenAI Experience
• Forward deployed engineering experience
• Machine Learning Experience

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.

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+.

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’s Robotics business unit is currently seeing historic levels of growth. As a Technical Program Manager (TPM) for Robotics Data, you will be the connective tissue across our most complex technical operations, driving initiatives that secure $XXM+ in new revenue.

This isn't a "sit back and watch" project management role. You will work with multiple project leads across a vast portfolio of robotics data projects, ensuring technical milestones are met, dependencies are de-risked, and stakeholders are aligned. You should be prepared to wear many hats and be excited about intense, impactful work that leads to accelerated career progression.

You will:

• Drive Multi-Project Outcomes: Serve as the primary driver for a portfolio of robotics projects, tracking milestones, deliverables, and dependencies to ensure on-time delivery for the world’s leading AI researchers.
• Bridge the Technical-Operational Gap: Act as the central liaison between AI clients, hardware engineers, and global operational teams to translate high-level goals into executable data collection workflows.
• Architect Scalable Pipelines: Partner with engineering to design and optimize end-to-end data ingestion pipelines, ensuring they can handle the high-fidelity sensor data (video, logs, teleop) required for Vision-Language-Action (VLA) models.
• Enforce Data Quality & Governance: Define KPIs and Quality Assurance (QA) metrics to ensure datasets are high-fidelity, labeled correctly, and compliant with rigorous privacy and safety standards.
• Standardize for Scale: Develop and refine Standard Operating Procedures (SOPs) that allow us to scale collection efforts across global, distributed teams.
• Communicate with Precision: Provide regular, data-driven progress updates to Scale’s executive team, utilizing SQL and dashboards to monitor performance and guide strategic pivots.

Ideally, you’d have:

• Strong Technical Foundation: A degree in Engineering, Computer Science, or a related field, combined with a deep understanding of AI/ML.
• 2-3+ Years of TPM Experience: Proven track record of managing complex, cross-functional technical programs, ideally in robotics, hardware, or large-scale data operations.
• Hands-on Problem Solving Skills: A proactive approach to overcoming technical and logistical roadblocks in a fast-paced environment.
• Operational Grit: Experience "in the weeds" of operational challenges - you don’t just identify bottlenecks; you build the solution to clear them.
• Entrepreneurial Mindset: You are comfortable with ambiguity and excited about building infrastructure from scratch in a fast-paced environment.

Nice to haves:

• SQL Proficiency: Ability to pull your own data and build your own tracking dashboards.
• Global Experience: Experience interacting with distributed teams or collection sites across different time zones.
• Robotics Domain Expertise: Familiarity with robotic hardware, sensor calibration, or the nuances of collecting data for Physical AI.
• AI/CV Knowledge: Familiarity with Computer Vision or Large Language Model (LLM) training requirements.

Scale’s mission is to accelerate the development of AI applications by providing the highest quality data. We believe that robust financial infrastructure is the backbone that allows our researchers and engineers to innovate at scale. Our Accounting team doesn't just record transactions; we build the systems that enable the next generation of AI breakthroughs.

We are looking for a Senior Manager, Technical Revenue Accounting to join our Accounting Team. In this role, you will be the primary orchestrator for revenue integrity at an innovative AI company. You will serve as a technical subject matter expert, architecting solutions for complex transactions and ensuring our financial systems scale as fast as our technology. If you are looking to make a significant impact at the intersection of frontier AI and financial infrastructure, come join us.

You will:

• Lead Revenue Accounting Team: Oversee monthly accounting close activities, including the review of complex journal entries and key account reconciliations including the management and development of a small team.
• Technical Oversight: Ensure strict compliance with ASC 606 and U.S. GAAP; serve as the final word on revenue recognition for both standard and highly bespoke contracts.
• Strategic Collaboration: Partner with Finance and Strategy teams on revenue metrics, flux analysis, and long-range forecasting.
• Audit Readiness: Lead the preparation of consolidated financial statements and footnotes; act as a primary point of contact for external auditors for all revenue related contracts and matters including developing footnotes and other financial reported items.

Ideally you'd have:

• Education: Bachelor’s degree in Accounting; CPA is highly preferred.
• Experience: 7+ years of progressive accounting experience, with a mix of Big 4 public accounting and high-growth industry experience (SaaS preferred).
• Leadership: 1+ years of experience managing and developing high-performing teams.
• Technical Rigor: Deep expertise in ASC 606 and the ability to translate complex technical research into actionable operational policies.
• Agility: A proven track record of problem-solving in a fast-moving, "ambiguity-heavy" environment.
• Systems Fluency: Experience with enterprise-level ERPs and revenue recognition software.

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.

The Public Sector software engineers (SWEs) create the core product building blocks forward-deployed teams use to develop agentic capabilities that function across multiple domains. SWEs responsibilities include building the systems required to ingest and process federal datasets to support real-time decision-making in contested environments. We develop novel agentic enabling capabilities that includes:

• Create multi-layered guardrails around agents
• Optimize data retrieval for agents
• Orchestrate fleets of asynchronous agents
• Automatically alerts users to deviations in data
• Illustrating how an agent reached a decision

As a Senior Software Engineer, you will lead the development of a vertical feature or a horizontal capability to include defining requirements with stakeholders and implementation until it is accepted by the stakeholders.

You will: Lead the design and implementation of scalable backend systems and distributed architectures for Federal customers.

• Manage the full lifecycle of feature development from requirement definition to deployment on classified networks.
• Direct the orchestration of asynchronous agent fleets to meet mission requirements.
• Lead customer engagements to translate mission needs into technical requirements.
• Own the communication with stakeholders to ensure implementation meets defined acceptance criteria.
• Conduct technical reviews and identify risks within machine learning infrastructure and model serving.
• Drive the platform roadmap by providing technical specifications for Federal product offerings.

Ideally you will have: 

• Full Stack Development: Proficiency in front-end, back-end development and infrastructure, including experience with modern web development frameworks, programming languages, and databases
• Cloud-Native Technologies: Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and experience in developing and deploying applications in a cloud-native environment. Understanding of containerization (e.g., Docker) and 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

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.

About Scale

At Scale AI, our mission is to accelerate the development of AI applications. For 8 years, Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including: generative AI, defense applications, and autonomous vehicles. With our recent Series F round, we’re accelerating the abundance of frontier data to pave the road to Artificial General Intelligence (AGI), and building upon our prior model evaluation work with enterprise customers and governments, to deepen our capabilities and offerings for both public and private evaluations.

About the ACE team 

The Agent Capabilities & Environments (ACE) team, part of Scale’s Research organization, brings together customer-facing Researchers and Applied AI Engineers. Our core mission includes research on agent environments and RL reward signals, benchmarking autonomous agent performance across real-world scenarios and environments, creating robust data programs to improve Large Language Models (LLMs) agentic capabilities and building foundational tools and frameworks for evaluating models as agents. ACE focuses on autonomous agents that dynamically interact with diverse external environments, including code repositories, GUI interfaces, browsers, and more. 

About This Role

This role is at the intersection of cutting-edge AI research and practical application, with a focus on studying the data types essential for building state-of-the-art agents, such as browser and SWE agents. The ideal candidate will explore the data landscape needed to advance intelligent, adaptable AI agents, guiding the data strategy at Scale to drive innovation. This position requires not only expertise in LLM agents and planning algorithms but also creativity in addressing novel challenges related to data, interaction, and evaluation. You will contribute to impactful research publications on agents, collaborate with customer researchers, and work alongside the engineering team to translate these advancements into real-world, scalable solutions.

Ideally you’d have: 

• Practical experience working with LLMs, with proficiency in frameworks like Pytorch, Jax, or Tensorflow. You should also be adept at interpreting research literature and quickly turning new ideas into prototypes.
• A track record of published research in top ML venues (e.g., ACL, EMNLP, NAACL, NeurIPS, ICML, ICLR, COLM, etc.)
• At least three years of experience addressing sophisticated ML problems, either in a research setting or product development.
• Strong written and verbal communication skills and the ability to operate cross-functionally. 

Nice to have:

• Hands-on experience with open source LLM fine-tuning or involvement in bespoke LLM fine-tuning projects using Pytorch/Jax. 
• Hands-on experience and publications in building applications and evaluations related to AI agents such as tool-use, text2SQL, browser agents, coding agents and GUI agents.
• Hands-on experience with agent frameworks such as OpenHands, Swarm, LangGraph, etc.
• Familiarity with agentic reasoning methods such as STaR and PLANSEARCH 
• Experience working with cloud technology stack (eg. AWS or GCP) and developing machine learning models in a cloud environment.

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.

Scale Labs, Research Scientist — Frontier Risk Evaluations

As the leading data and evaluation partner for frontier AI companies, Scale plays an integral role in understanding the capabilities and safeguarding AI models and systems. Building on this expertise, Scale Labs has launched a new team focused on policy research, to bridge the gap between AI research and global policymakers to make informed, scientific decisions about AI risks and capabilities.

Our research tackles the hardest problems in agent robustness, AI control protocols, and AI risk evaluations to help governments, industry, and the public understand and mitigate AI risk while maximizing AI adoption. This team collaborates broadly across industry, the public sector, and academia and regularly publishes our findings. We are actively seeking talented researchers to join us in shaping this vision.

As a Research Scientist focused on Frontier Risk Evaluations, you will design and create evaluation measures, harnesses and datasets for measuring the risks posed by frontier AI systems. For example, you might do any or all of the following: 

• Design and build harnesses to test AI models and systems (including agents) for dangerous capabilities such as security vulnerability exploitation, CBRN uplift, and other high-risk activities;
• Work with government agencies or other labs to collectively scope and design evaluations to measure and mitigate risks posed by advanced AI systems;
• Publish evaluation methodologies and write technical reports for policymakers.

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 instrumenting ML pipelines, writing evaluation harnesses, and quickly turning new ideas from the research literature into working prototypes.
• 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:

• Experience in crafting evaluations and benchmarks, or a background in data science roles related to LLM technologies.
• Experience with red-teaming or adversarial testing of AI systems.
• Familiarity with AI safety policy frameworks (e.g., NIST AI RMF, EU AI Act, Korea AI Basic Act).

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.

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 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 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!)

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.

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.

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.

The Enterprise ML team works on the front lines of the AI revolution, partnering deeply with customers to identify high-impact business problems and build cutting-edge AI systems using Scale’s proprietary research, data, and infrastructure—unlocking domain expertise through high-quality data and expert feedback.

As Director of Enterprise ML, 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.

This role is ideal for a leader who thrives in ambiguity, understands both frontier GenAI capabilities and their limitations, and is motivated by turning research into durable, production-ready systems.

What You’ll Do

• 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.

What We’re Looking For

Core Qualifications

• 8+ 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.
• Exceptional communication and stakeholder management skills, with the ability to influence executives, customers, and cross-functional partners

Nice to Have

• Hands-on experience building and deploying agent-based, tool-augmented, or workflow-driven LLM systems in enterprise environments
• Prior ownership of enterprise AI platforms, internal ML products, or customer-facing AI services at scale
• Proven track record of partnering directly with enterprises to identify high-impact use cases and deliver measurable business outcomes

The GTM Architect, Enterprise will report to the Head of Enterprise GTM and will own the operating systems, measurement, and engagement model that power Scale AI’s enterprise revenue motion. This role is responsible for designing and running the enterprise GTM architecture across RevOps, sales performance, and cross-functional execution, ensuring Scale’s largest and most strategic accounts are engaged with rigor, consistency, and impact.

This is a senior, highly visible role that partners closely with Enterprise Sales leadership, Finance, Marketing, Product, and Solutions Engineering. The GTM Architect will bring a strong point of view on how Scale engages enterprise accounts, how performance is measured, and how teams operate day-to-day to drive predictable growth. Over time, this role will have the opportunity to build and lead a GTM / RevOps team.

In this role, you will:

• Own and evolve Scale’s enterprise GTM operating model, including account engagement strategy, funnel design, and sales execution standards
• Design and manage the enterprise RevOps systems stack (e.g., CRM, forecasting, reporting, planning tools) to support scalable growth
• Define, track, and operationalize core enterprise GTM metrics across pipeline health, deal velocity, forecast accuracy, and rep productivity
• Establish and run sales operating cadences including pipeline reviews, forecast calls, QBRs, and performance reviews
• Partner with Sales Leadership and Finance to design, implement, and maintain enterprise sales compensation plans, including quota governance and attainment reporting
• Build executive-level dashboards and reporting to support GTM decision-making and leadership visibility
• Serve as a strategic thought partner to Enterprise Sales leaders, bringing a strong opinion on how accounts should be covered, prioritized, and engaged
• Act as the connective tissue across Sales, Marketing, Finance, Product, and Solutions Engineering for enterprise GTM planning and execution
• Support annual and quarterly planning efforts including territory design, capacity modeling, headcount planning, and quota setting
• Ensure data integrity, process clarity, and operational discipline across all enterprise GTM motions
• Initially operate as a senior individual contributor, with a clear path to hiring, developing, and leading a high-impact GTM / RevOps team

Ideally, You Will Have:

• 8–12+ years of experience in RevOps, Sales Ops, or GTM Strategy roles, with deep exposure to enterprise sales environments
• Experience supporting complex, multi-stakeholder enterprise sales motions in high-growth B2B SaaS or platform companies
• Proven ownership of sales systems, forecasting, and performance measurement at scale
• Hands-on experience designing and managing enterprise sales compensation plans and reporting
• Strong understanding of enterprise GTM metrics, planning cycles, and operating cadences
• A clear point of view on how enterprise accounts should be engaged and how to operationalize that engagement at scale
• Comfort influencing senior sales leaders and executives without direct authority
• Excellent written and verbal communication skills, including experience building executive-level materials and dashboards
• Strong command of GTM systems and tools (e.g., Salesforce, Clari, planning and reporting tools)
• High attention to detail paired with the ability to operate at a strategic altitude
• Demonstrated ability to operate as a senior IC with the ambition and capability to build and lead a team over time
• Technical curiosity or experience working alongside technical products and teams; familiarity with AI, ML, or data platforms is a plus

Scale's Generative AI business is continuing to see tremendous growth and expansion. Engagement Managers (EMs) are the combination of externally customer-facing and internally operationally driven. In this role, you will operate at the center of Scale's most strategic customer relationships, serving as both a trusted operator and thought partner to the world's leading AI research teams. 

You are the frontline of Scale’s contact with our Gen AI customers, working with and being an advocate for customer data leaders and engineering/operations teams. You have a strong interest in how high-quality data can positively influence Gen AI models. You work towards finding not just one-off solutions, but repeatable and scalable ways to ensure we continually deliver.

The ideal candidate builds deep relationships with researchers and customer leads, navigates difficult conversations with confidence, and has a track record of earning new work through the quality of their execution and relationships. They are naturally empathetic and excel at building long-term relationships through diligent problem solving and thoughtful, strategic discussions.

You will:

• Own a portfolio of complex, strategic projects with full accountability for delivery, quality, customer sentiment, and commercial outcomes
• Build and maintain deep, trust-based relationships with customer researchers and leads, serving as a thought partner throughout the project lifecycle
• Navigate difficult customer conversations around pricing, quality, and delivery expectations with confidence and clarity
• Identify and develop expansion opportunities through close customer engagement and a strong track record of execution

Ideally you'd have:

• 5+ years of work experience, with experience in consulting or as a technical product or program management role
• A proven track record in B2B client-facing roles, including building and expanding relationships and navigating complex customer dynamics
• Ability to understand the ML training lifecycle and discuss use cases meaningfully with technical customers
• A technical background (education or professional experience with CS, Engineering, Economics, Statistics, or another STEM field)

Nice to haves:

• Graduate degree (PhD, MS) or research experience in a STEM field
• Experience at a frontier lab or company developing foundational models, or in a technical role at a high-growth AI company
• Hands-on technical experience working with data or AI/ML models, whether through engineering, research, or a technical product role

Scale's Generative AI business is continuing to see tremendous growth and expansion. Engagement Managers (EMs) are the combination of externally customer-facing and internally operationally driven. In this role, you will be the primary owner of the customer relationship, managing ongoing projects and driving end-to-end engagements from new projects and pilots, owning the account execution, working cross-functionally to ensure Scale products and services are delivered consistently and on-time. Within Scale you represent the customer, aligning their objectives to how Scale's operations and product teams execute and deliver.

The ideal candidate is organized, execution-focused, and thrives on managing complexity. Precision across tracking, documentation, quality alignment, and customer follow-through is what makes customers successful and builds the trust that earns Scale more work. You will be on the front lines of ensuring that these customers become passionate, lifelong Scale partners.

You will:

• Own end-to-end execution and delivery for assigned customer projects, from kickoff through completion and quality feedback
• Manage customer communication, action items, and follow-ups across multiple concurrent projects
• Monitor delivery against SLAs, budget, and quality standards, proactively identifying risks and escalating blockers with proposed solutions
• Review, track and improve operational performances and be obsessed with continuous improvement
• Partner cross-functionally with operations and planning teams to improve delivery efficiency and drive better outcomes for customers

Ideally you'd have:

• 3 to 5 years of work experience, with experience in consulting, technical program management, or project coordination
• A track record of managing multiple concurrent workstreams with strong attention to detail and follow-through
• Experience in B2B client-facing roles where execution and delivery were core responsibilities
• An action-oriented mindset that balances creative problem solving with the scrappiness to ultimately deliver results
• A technical background (education or professional experience with CS, Engineering, Economics, Mathematics, or another STEM field)

Nice to haves:

• Familiarity with model and AI training workflows
• Work experience in a high-growth company environment, including working cross-functionally and wearing multiple hats

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.

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 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'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

As a Software Engineer on the Machine Learning Infrastructure team, you will build the "Operating System" for our large-scale GPU clusters. You will architect a high-performance training platform that handles the immense complexity of multi-thousand GPU workloads, ensuring every cycle is used efficiently. Your work directly determines the velocity at which our researchers can train and iterate on the world’s most advanced models.

The ideal candidate is a systems expert who thrives on solving the orchestration, networking, and reliability challenges that emerge at massive scale. You will partner closely with researchers to build a seamless, resilient environment that transforms raw compute into breakthrough AI.

You will:

• Architect and scale a multi-tenant orchestration layer that abstracts away the complexity of GPU clusters, ensuring high utilization and seamless job recovery.
• Design and implement scheduling primitives to optimize the lifecycle of training jobs.
• Develop deep observability and automated health-checking into the training stack to proactively identify and isolate hardware failures
• Evaluate and integrate emerging technologies in the CNCF and AI ecosystem (e.g. Ray, Kueue), making data-driven build vs. buy decisions that balance velocity with long-term maintainability.
• Work closely with Finance and Procurement teams to drive our capacity planning process.
• Participate in our team’s on call process to ensure the availability of our services.
• Own projects end-to-end, from requirements, scoping, design, to implementation, in a highly collaborative and cross-functional environment.

Ideally you'd have:

• 5+ years of experience in backend or infrastructure engineering, with at least 2 years focused on orchestrating ML workloads at scale (100+ GPU nodes).
• Strong programming skills in one or more languages (e.g. Python, Go, Rust, C++)
• Experience with complex compute management systems that cover queueing, quotas, preemption, and gang scheduling.
• Experience with distributed training infrastructure, such as EFA, Infiniband, and topology-aware scheduling.
• Experience with distributed storage systems (e.g. Lustre, S3) as they relate to training throughput
• Expert-level knowledge of Kubernetes internals (Custom Resources, Operators, Admission Controllers) and how they interact with device plugins for specialized hardware.
• Familiarity with cloud infrastructure (AWS, GCP) and infrastructure as code (e.g., Terraform).
• Proven ability to solve complex problems and work independently in fast-moving environments.

Nice to haves:

• Experience with distributed training techniques such as DeepSpeed, FSDP, etc.
• Experience with the NVIDIA software and hardware stack (CUDA, NCCL)
• Experience with PyTorch
• Familiarity with post-training algorithms such as GRPO, and with Reinforcement Learning

As a Software Engineer on the ML Infrastructure team, you will design and build platforms for scalable, reliable, and efficient serving of LLMs. Our platform powers cutting-edge research and production systems, supporting both internal and external use cases across various environments.

The ideal candidate combines strong ML fundamentals with deep expertise in backend system design. You’ll work in a highly collaborative environment, bridging research and engineering to deliver seamless experiences to our customers and accelerate innovation across the company.

You will:

• Build and maintain fault-tolerant, high-performance systems for serving LLMs workloads at scale.
• Build an internal platform to empower LLM capability discovery.
• Collaborate with researchers and engineers to integrate and optimize models for production and research use cases.
• Conduct architecture and design reviews to uphold best practices in system design and scalability.
• Develop monitoring and observability solutions to ensure system health and performance.
• Lead projects end-to-end, from requirements gathering to implementation, in a cross-functional environment. 

Ideally you'd have:

• 5+ years of experience building large-scale, high-performance backend systems.
• Strong programming skills in one or more languages (e.g., Python, Go, Rust, C++).
• Experience with LLM serving and routing fundamentals (e.g. rate limiting, token streaming, load balancing, budgets, etc.)
• Experience with LLM capabilities and concepts such as reasoning, tool calling, prompt templates, etc.
• Experience with containers and orchestration tools (e.g., Docker, Kubernetes).
• Familiarity with cloud infrastructure (AWS, GCP) and infrastructure as code (e.g., Terraform).
• Proven ability to solve complex problems and work independently in fast-moving environments.

Nice to haves:

• Experience with modern LLM serving frameworks such as vLLM, SGLang, TensorRT-LLM, or text-generation-inference.

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.

Senior Machine Learning Engineer - Model Evaluations, Public Sector

The Public Sector ML team at Scale deploys advanced AI systems—including LLMs, agentic models, and multimodal pipelines—into mission-critical government environments. We build evaluation frameworks that ensure these models operate reliably, safely, and effectively under real-world constraints. As an ML Engineer, you will design, implement, and scale automated evaluation pipelines that help customers trust and operationalize advanced AI systems across defense, intelligence, and federal missions.

You will:

• Develop and maintain automated evaluation pipelines for ML models across functional, performance, robustness, and safety metrics, including LLM-judge–based evaluations.
• Design test datasets and benchmarks to measure generalization, bias, explainability, and failure modes.
• Build evaluation frameworks for LLM agents, including infrastructure for scenario-based and environment-based testing.
• Conduct comparative analyses of model architectures, training procedures, and evaluation outcomes.
• Implement tools for continuous monitoring, regression testing, and quality assurance for ML systems.
• Design and execute stress tests and red-teaming workflows to uncover vulnerabilities and edge cases.
• Collaborate with operations teams and subject matter experts to produce high-quality evaluation datasets.
• Comfortable with light travel (approximately 10%) for customer interaction and team needs.

This role will require an active security clearance or the ability to obtain a security clearance.

Ideally you’d have:

• Experience in computer vision, deep learning, reinforcement learning, or NLP in production settings.
• Strong programming skills in Python; experience with TensorFlow or PyTorch.
• Background in algorithms, data structures, and object-oriented programming.
• Experience with LLM pipelines, simulation environments, or automated evaluation systems.
• Ability to convert research insights into measurable evaluation criteria.

Nice to haves:

• Graduate degree in CS, ML, or AI.
• Cloud experience (AWS, GCP) and model deployment experience.
• Experience with LLM evaluation, CV robustness, or RL validation.
• Knowledge of interpretability, adversarial robustness, or AI safety frameworks.
• Familiarity with ML evaluation frameworks and agentic model design.
• Experience in regulated, classified, or mission-critical ML domains.

The goal of a Senior Machine Learning Engineer at Scale is to leverage techniques in the fields of generative AI, computer vision, reinforcement learning, and agentic AI to improve Scale's products and customer experience in production environments. Our machine learning engineers take advantage of robust internal infrastructure and  unique access to massive datasets to deliver improvements to our customers.

Our Public Sector Machine Learning team is focused on deploying cutting-edge models to mission-critical government systems through products like Donovan and Thunderforge. Our work spans multiple modalities, with a strong focus on both large language models and computer vision. On the LLM side, we are developing agentic systems that help solve complex operational and planning challenges for government partners. This includes building agent frameworks that integrate with custom retrieval pipelines and production APIs, as well as evaluation tools to benchmark and refine agent behavior. We're also advancing research in areas like reinforcement learning for agentic LLMs, with successful deployment into real-world operational environments. On the computer vision front, we're training advanced models to increase labeling throughput and automate perception tasks. Our efforts include building large-scale fine-tuning pipelines, training models across multiple modalities, and developing generalizable vision foundation models to support a wide range of defense applications.

You will:

• Take state of the art models developed internally and from the community, use them in production to solve problems for our customers and taskers
• Improve and maintain production models through retraining, hyperparameter tuning, and architectural updates, while preserving core performance characteristics
• Collaborate with product and research teams to identify and prototype ML-driven product enhancements, including for upcoming product lines
• Work with massive datasets to develop both generic models as well as fine tune models for specific products
• Build scalable machine learning infrastructure to automate and optimize our ML services
• Serve as a cross-functional representative and advocate for machine learning techniques across engineering and product organizations
• Be comfortable learning new technologies quickly and managing multiple priorities in a fast-paced environment
• Comfortable with light travel (approximately 10%) for customer interaction and team needs
• This role will require an active security clearance or the ability to obtain a security clearance

Ideally You’d Have:

• Extensive experience with GenAI, Agentic AI, natural language processing, deep learning and deep reinforcement learning, or computer vision in a production environment
• Solid background in algorithms, data structures, and object-oriented programming
• Strong programing skills in Python, experience in Tensorflow or PyTorch

Nice to Haves:

• Graduate degree in Computer Science, Machine Learning or Artificial Intelligence specialization
• Experience working with cloud platforms (eg. AWS or GCP) and deploying machine learning models in cloud environments
• Experience with computer vision, generative AI models, large language models, or agentic systems
• Familiarity with ML evaluation frameworks and agentic model design

Scale's public sector business is providing the best of American commercial technology and innovation to protect the homeland and meet the moment. As a member of our public sector delivery team, you will own relationships critical to the portfolio of clients charged with a layered defense for the United States. You will be a catalyst, willing to go deep, get technical, and drive change. You will manage customer relationships and partners as well as partner with our engineering team to solve Scale’s hardest problems. All of this serves an ultimate goal of delivering cutting-edge agentic AI to orchestrate portfolio management for defense of the homeland.

You will:

• Drive innovation and transformation by diving deep into technical and operational challenges, solving undefined problems, and delivering impactful agentic AI solutions
• Transition AI/ML technologies and processes into working products / solutions even when requirements are undefined or ambiguous
• Partner with Scale engineering, operations, and other public sector teams to build and deliver AI systems tailored to unique government use cases in the computer vision and generative AI domains
• Lead a cross-functional team to exceed the customer’s AI/ML objectives
• Support and partner across B2B and B2G organizations to achieve the outcomes in delivering the greater layered defense for the United States

We have a diverse team with a variety of skill sets, many have:

• 5+ years of professional experience, often in a customer-facing technical program management role in industry or government.
• A proven track record in B2B or government client facing roles and expanding client relationships
• Prior experience leading engagements with government customers

Must haves:

• An active TS/SCI clearance
• Minimum of 3 years of work experience leading teams / programs in industry or government 
• A basic understanding of ML operations process
• A track record of structured, analytics-driven problem-solving
• Excellent verbal and written communication skills
• Willingness to travel at least 25% of the time

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.

About our AgentOps team: 

The vision for the AgentOps team is to build the best Agent Development Platform in the AI Industry.

Agent Development is in its nascent stages in a rapidly changing industry, with limited tooling making it hard for agent developers to manage agent lifecycles. As a team that has a front-row seat to what Enterprise customers need and want, we want to build an opinionated but flexible platform for all Agent operations ("AgentOps"), including building, deploying, monitoring, evaluating and improving agents to solve customer needs.

With the AI industry currently moving towards RL workflows that need verifiable rewards, we further want to gear this platform towards knowledge capture that create compounding effects to make Agents more effective and capable. We want to create a virtuous data flywheel where agents built using this platform see continuous performance improvements and increase customer value over time.

We are a rapidly growing team with ambitious goals, and are looking for motivated individuals to join us to make an impact in a green-field domain.

Responsibilities:

• Manage the engineering team and drive technical delivery
• Comfortable working cross functionally, whether that be internal or external customers
• Work across the entire product lifecycle from conceptualization through production
• Build features end-to-end: back-end, system design, debugging and testing
• Deliver experiments at a high velocity and level of quality to engage our customers
• Influence the culture, values, and processes of a growing engineering team
• Inspire and mentor engineers
• Collaborating with cross-functional teams to define, design, and ship new product features and experiences

Requirements:

• At least 5 years of relevant experience and at least 2 years of experience managing engineers is preferred
• Proven success in leading, managing, and developing high-performing Engineering teams
• Expertise in identifying product engagement patterns and trends for large scale consumer products
• Track record of shipping high-quality products and features at scale
• Desire to work in a very fast-paced environment
• Ability to turn business and product ideas into engineering solutions
• Excellent problem-solving skills, and be able to work independently or as part of a team.
• Excited to join a dynamic, hybrid team in either San Francisco or New York City.

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 is seeking a highly skilled and motivated Software Engineer, ARC (Architecture, Reliability, & Compute) to join our dynamic Public Sector Engineering team. As a part of this team, you will define how the company ships software, establishing the patterns for deploying into complex government and high-security environments, rather than just running Terraform scripts. You will build and maintain internal CLIs/tools that standardize testing, deployment, environment management and are tools that engineering relies on to prevent downstream breakages. You will execute on automated deployment efforts to pay down tech debt, creating fully functional staging/testing environments, and defining the company's standard for safe deployments.

You will:

• Design and implement secure scalable backend systems for Public Sector customers, leveraging Scale's modern and cloud-native AI infrastructure.
• Own services or systems and define their long-term health goals, while also improving the health of surrounding components.
• Re-architect the stack to run in compliant or restrictive environments. This requires designing swappable components (auth, storage, logging) to meet government/security mandates without breaking the product.
• 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.
• Participate actively in customer engagements, working closely with stakeholders to understand requirements and deliver innovative solutions.
• Contribute to the platform roadmap and product strategy for Scale AI's Public Sector business, playing a key role in shaping the future direction of our offerings.

Must have:

• At least an active secret clearance and the ability & willingness to up level to TS/SCI with CI Poly. This is a requirement and candidates will not be considered who do not hold at least a secret clearance

Ideally you'd have:

• Full Stack Development: Proficiency in both front-end and back-end development, including experience with modern web development frameworks, programming languages, and databases. Experience with developing & delivering software to air-gapped & isolated environments is a plus.
• Cloud-Native Technologies: Understanding of containerization (e.g., Docker) and container orchestration (e.g., Kubernetes) is desired. Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and experience in developing and deploying applications in a cloud-native environment. 
• Security Focused: Experience with Federal Compliance frameworks, and requirements(e.g, Cloud SRG, FedRAMP, STIG Benchmarks, etc). Experience developing software & technical solutions that meet strict security & regulatory compliance requirements.
• 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 evolving project requirements. Ability to quickly grasp and apply new concepts and stay up-to-date with emerging trends in software engineering.
• Must be able to support work 3-4 days a week from the DC, SF, NYC, or STL office.

The Enterprise Account Executive will report to the Director of Enterprise GTM and will own revenue growth across a portfolio of Scale AI’s largest and most strategic enterprise customers. This role is focused on selling complex, highly technical AI solutions into F500 organizations, partnering with executive, technical, and operational stakeholders to drive long-term value and expansion.

You will be responsible for full-cycle enterprise sales - from prospecting and deal strategy through close, renewal, and expansion - while serving as the quarterback across internal teams including Solutions Engineering, Product, Research, and Operations. This role requires strong ownership, executive presence, and the ability to navigate multi-stakeholder enterprise buying processes in a fast-paced environment. 

You Will:

• Own and drive relationships with Scale’s largest and most complex Fortune 500 prospects and customers
• Build trusted relationships with executive, technical, and operational stakeholders across multiple business units
• Develop and execute comprehensive account strategies to drive net-new revenue, expansion, and long-term partnerships
• Lead strategic deal planning and mutual close plans across new business, renewals, and expansions
• Partner closely with Solutions Engineering and Product teams to deliver compelling, technically credible value propositions
• Act as the voice of the customer internally, influencing product roadmap, research priorities, and delivery execution
• Maintain deep understanding of customer business goals, AI maturity, and industry trends to proactively identify opportunities
• Consistently communicate account health, pipeline, and forecast accuracy using Salesforce, Clari, and related tools
• Thrive in a fast-moving, multi-threaded environment while maintaining strong attention to detail and prioritization

Ideally, You Will Have:

• 8+ years of enterprise sales or account management experience, including 2+ years selling deeply technical solutions to both business and technical audiences
• A proven track record of closing and expanding large, complex enterprise deals 
• Demonstrated success consistently achieving or exceeding quota in enterprise sales roles
• Experience building and executing long-term account strategies to drive sustained revenue growth
• Strong ability to lead enterprise renewal processes from strategy through close
• Excellent written and verbal communication skills, with comfort presenting to executive audiences
• Strong command of enterprise sales processes and systems (Salesforce, Clari, Outreach, Slack)
• A consultative, customer-first mindset with the ability to influence cross-functional internal teams
• Experience developing executive-level materials and business cases
• Strong project management, organizational skills, and attention to detail
• Technical background or strong technical curiosity highly valued, especially familiarity with AI, ML, or data platforms

Sales Commission: This role is eligible to earn commissions.

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

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

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.

Scale is a vital part of bringing AI-enabled technologies to the world, from autonomous driving to drones, robots, and large language models. For example, Scale works with the world's top self-driving car and robotics ML teams as well as the largest companies in the generative AI space. 

As our customer base is growing, you will be on the front lines 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.

Our Field Engineers ensure customers' experiences with Scale's technology are seamless and optimized to build a successful, long-term partnership. Field Engineers partner closely with Product, Engineering, and Operations to lead existing customers through building production-grade data pipelines. We do this by knowing our customer’s use-cases inside and out, and creating the tooling and documentation needed to scalably support their growth.

Field Engineers in general are experts on Scale's products and codebase, and have general technical knowledge on web development, using APIs, and working with large volumes of data. Field Engineers are strong relationship builders, great project managers, and always fun to work with. 

The ideal person is a software engineer generalist who enjoys working with clients directly, taking ambiguous requirements and issues, and quickly designing and building sustainable solutions in close collaboration with the Product and Engineering teams. This role is at the intersection of customer delivery, product, and engineering, giving you a breadth of experience and fully leveraging both sides of your brain. If this sounds like you, we invite you to apply!

You will:

• Implement end-to-end data integrations, syncing customer’s data to Scale’s platform and back
• Work closely with our customer’s engineering teams to optimize data pipelines, including providing input towards designing API endpoints and input/output schemas
• Design, develop and maintain playbooks, internal tools, Scale’s documentation and SDKs to quickly get customers set up for long-term success
• Partner with Software Engineers and Operations to remove any technical hurdles customers may face / Debug technical issues impacting delivery and own technical escalations coming from the customer
• Be accountable for the customer’s technical experience throughout their time with Scale
• Work with AEs and PMs to identify customer-specific feature requests
• Develop technical domain expertise in areas of Large Language Models, 2D Image Annotation, and working with API integrations
• Evangelize Scale and interact with customers at major events
• Have an active TS/SCI clearance

Ideally you'd have:

• Track record of success as a hybrid customer-facing engineer or similar function, wearing multiple hats along the way
• Prior technical hands-on experience working with clients in a pre or post-sales capacity to realize business goals
• Prior experience developing with Python and JavaScript, or other modern software languages
• Strong engineering background preferably in Computer Science, Mathematics, or other quantitative fields
• Strong project management and interpersonal skills
• Presentation skills with a high degree of technical credibility when speaking with executives and front-line engineers
• High level of comfort communicating effectively across internal and external organizations
• Intellectual curiosity, empathy, and ability to operate with high velocity

Nice to haves:

• Experience in AI
• Experience working in classified environments
• Previous experience as a technical go-to-market resource
• Understanding of DevSecOps principles, including secure software delivery, infrastructure as code, and continuous integration/deployment
• Hands-on knowledge of container orchestration with Kubernetes and experience with Helm charts for application deployment
• Experience automating infrastructure and configuration management using Ansible or similar tools

About Scale AI

Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with leading enterprises and government organizations to accelerate their AI initiatives through our data annotation platform, generative AI solutions, and enterprise AI capabilities.

Role Overview

As a Forward Deployed AI Engineering Manager on our Enterprise team, you'll be the technical bridge between Scale AI's cutting-edge AI capabilities and our most strategic customers. You'll work with enterprise clients to understand their unique challenges, lead a team that architects specific AI solutions, and ensure successful deployment and adoption of AI systems in production environments.

This is a Management role that combines deep engineering and AI expertise, leading a team, and working on customer-facing problems. You'll work directly with customer engineering teams to integrate AI into their critical workflows.

Key Responsibilities

Customer Integration & Deployment

• Partner directly with enterprise customers to understand their technical infrastructure, data pipelines, and business requirements
• Design and implement custom integrations between Scale AI's platform and customer data environments (cloud platforms, data warehouses, internal APIs)
• Build robust data connectors and ETL pipelines to ingest, process, and prepare customer data for AI workflows
• Deploy and configure AI models and agents within customer security and compliance boundaries

AI Agent Development

• Develop production-grade AI agents tailored to customer use cases across domains like customer support, data analysis, content generation, and workflow automation
• Architect multi-agent systems that orchestrate between different models, tools, and data sources
• Implement evaluation frameworks to measure agent performance and iterate toward business objectives
• Design human-in-the-loop workflows and feedback mechanisms for continuous agent improvement

Prompt 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

Leadership & Collaboration

• Serve as the Engineering Manager and technical point of contact for strategic enterprise accounts
• Lead a team that is collaborating with customer data scientists, ML engineers, and software developers to ensure smooth integration
• 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

• 5+ years of software engineering experience with 2+ yrs of  Management 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.

About Scale AI

At Scale AI, our mission is to accelerate the development of AI applications. For 8 years, Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including generative AI, defense applications, and autonomous vehicles. With our recent Series F round, we’re accelerating the abundance of frontier data to pave the road to Artificial General Intelligence (AGI) and building upon our prior model evaluation work with enterprise customers and governments to deepen our capabilities and offerings for public and private evaluations.

About Data Engine

Our Generative AI Data Engine powers the world’s most advanced LLMs and generative models through world-class RLHF (Reinforcement Learning with Human Feedback), human data generation, model evaluation, safety, and alignment. The data we produce is some of the most critical work for how humanity will interact with AI.

About Our FDE Team

Generating high-quality data is the core problem our business solves. We aim to make producing and delivering high-quality data seamless and efficient for operators and customers. Our Team is building customer and operator-specific infrastructure to provide high-quality data with low turnaround time. You'll be exposed to the cutting edge of the Generative AI industry while directly interfacing with the leading model-building organizations in the space, including the top AI research labs and government agencies. 

Join us in shaping the future of Artificial General Intelligence. As a Forward Deployed Engineer, you'll be at the forefront of providing the critical data infrastructure that powers the most advanced AI models, directly influencing how humanity interacts with AI. You will work with the world’s leading AI companies and government agencies to solve their most complex AI data-related problems.

Responsibilities:

• Drive Impact: Directly contribute to the advancement of AI by delivering critical data solutions for leading AI innovators and government agencies.
• Customer Collaboration: Interact daily with our technical customers, understanding their unique challenges and translating them into impactful solutions.
• End-to-End Development: Design, build, and deploy features across the entire stack, from front-end interfaces to back-end systems and infrastructure.
• Rapid Experimentation: Deliver high-quality experiments quickly, iterating quickly to meet customer needs and drive innovation.
• Strategic Influence: Play a key role in shaping our engineering culture, values, and processes, contributing to the growth of our team and the evolution of our product.
• Diverse Projects: Engage in a dynamic mix of designing and deploying cutting-edge data solutions, collaborating with leading AI researchers, and directly influencing the product roadmap. You'll work on everything from large-scale system architecture to customer-facing front-end application design.
• Leadership Growth: This role offers a unique opportunity to lead critical projects, shape our engineering culture, and accelerate your career growth in the rapidly evolving field of Generative AI. You'll be positioned to become a future leader in a company defining the next era of technology.

Requirements:

• At least 2 years of relevant experience is preferred
• Proven track record of shipping high-quality products and features at scale.
• Strong problem-solving skills and the ability to work independently or as part of a collaborative team.
• Desire to thrive in a fast-paced, dynamic environment.
• Ability to turn business and product ideas into engineering solutions.
• Strong coding abilities and the ability to effectively communicate complex technical concepts to both technical and non-technical audiences.
• Ability to adapt quickly to the ever-changing world of generative AI.
• Excited to join a dynamic, hybrid team in either San Francisco or New York City.

Preferred Qualifications:

• Experience with large-scale data processing and distributed systems.
• Familiarity with machine learning and AI concepts.
• Experience working directly with enterprise customers.
• Experience with cloud-based infrastructure.

Scale GP (Scale Generative AI Platform) is an enterprise-grade Generative 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 product 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 be responsible for owning large new areas within our product, working across backend, frontend, and interacting with LLMs and ML models. You will solve hard engineering problems in scalability and reliability.

You will:

• Own large new areas within our product
• Work across backend, frontend, and interacting with LLMs and ML models
• 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

Ideally you'd have:

• 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)

Job Description: Distinguished Engineer, Enterprise AI 

About Scale AI

Our mission is to develop reliable AI systems for the world's most important decisions. The Enterprise AI business delivers performant, reliable, and production-grade AI applications to enterprises across all industries by providing Generative AI expertise and infrastructure.

The Role

We’re seeking a Distinguished Engineer - a hands-on technical leader operating at the VP level - to shape the vision and technical roadmap of our core AI/ML infrastructure that powers enterprise AI applications. Reporting directly to the SVP of Engineering, Enterprise AI, this individual will drive long-term technical direction for our Scale GenerativeAI Platform (SGP), influence architectural decisions across the company, and partner closely with engineering and product leaders to bring advanced AI capabilities to enterprise customers.

You’ll serve as a cross-organizational thought leader - setting standards for technical excellence, mentoring senior engineers, and ensuring our systems and models meet the demands of global-scale deployment. This is a rare opportunity to influence both foundational AI infrastructure and the enterprise AI applications built on top of it.

Responsibilities

• Define and drive the technical strategy for Scale’s AI/ML infrastructure and SGP platform, balancing short and long-term investments.
• Partner with senior engineering and product leadership to ensure scalable, secure, and performant enterprise AI systems.
• Lead architecture and design reviews across multiple teams, ensuring technical consistency and innovation.
• Serve as a trusted advisor and mentor to principal engineers and technical leads across the organization.
• Evaluate and integrate emerging technologies in AI, distributed systems, and data infrastructure to keep Scale at the frontier of innovation.
• Represent Scale externally in the AI community - through speaking engagements, partnerships, and thought leadership.
• Drive technical execution and accountability for critical cross-functional initiatives that advance Scale’s enterprise AI capabilities.

Qualifications

• 15+ years of experience as a technical software engineering leader.
• Proven record of technical leadership at AI-native companies, hyperscalers, or equivalent high-scale environments.
• Deep technical expertise in AI/ML infrastructure, knowledge of ML models/algorithm design/implementation and their application to real-world problems; experience with GenAI preferred.
• Demonstrated success in setting technical vision and leading cross-organizational initiatives with measurable business impact.
• Experience influencing and mentoring engineering teams in complex, matrixed environments.
• Ability to communicate and collaborate effectively to create a shared sense of vision or purpose cross-team and cross-functionality.
• Advanced degree in Computer Science, Engineering, or related field preferred but not required.

Culture & Impact

At Scale, we believe that AI should amplify human potential - and our engineering culture reflects that belief. Our teams operate at the intersection of innovation, rigor, and impact, solving some of the hardest problems in AI infrastructure and deployment.

The Distinguished Engineer will play a key role in shaping how AI systems are built, deployed, and governed within enterprise environments. This role represents the highest bar of technical excellence at Scale - a trusted voice in setting direction, enabling innovation, and ensuring that our technology scales responsibly and effectively to meet the evolving needs of our customers.

You’ll have the opportunity to influence company-wide strategy, contribute to industry-leading work in generative AI infrastructure, and mentor the next generation of engineering talent pushing the boundaries of what’s possible with AI.

Scale AI is seeking a highly skilled and motivated Software Engineer, Frontier AI Infrastructure to join our dynamic Public Sector Engineering team. As a part of this team, you will own the model inference layer - enabling state of the art models, debugging the latest AI tools, managing networking, debugging latency, and tracking pricing/usage metrics for AI models. You will lead technical discussions on the frontlines with cloud vendors and customers to deliver on critical contracts and to debug platform issues. You will also work upstream with Product to understand features before they break, moving us from "infra-only debugging" to proactive integration testing.

You will:

• Design and implement secure scalable backend systems for Public Sector customers, leveraging Scale's modern and cloud-native AI infrastructure.
• Own services or systems and define their long-term health goals, while also improving the health of surrounding components
• Re-architect the stack to run in compliant or restrictive environments. This requires designing swappable components (auth, storage, logging) to meet government/security mandates without breaking the product.
• You will work with Product to build integration tests that catch issues early, shifting the focus from "infra-only debugging" to preventing failures upstream.
• Participate actively in customer engagements, working closely with stakeholders to understand requirements and deliver innovative solutions.
• Contribute to the platform roadmap and product strategy for Scale AI's Public Sector business, playing a key role in shaping the future direction of our offerings.

Must have:

• At least an active secret clearance and the ability & willingness to up level to TS/SCI with CI Poly. This is a requirement and candidates will not be considered who do not hold at least a secret clearance

Ideally you'd have: 

• Full Stack Development: Proficiency in both front-end and back-end development, including experience with modern web development frameworks, programming languages, and databases. Experience with developing & delivering software to air-gapped & isolated environments is a plus.
• Cloud-Native Technologies: Understanding of containerization (e.g., Docker) and container orchestration (e.g., Kubernetes) is desired. Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and experience in developing and deploying applications in a cloud-native environment. 
• Security Focused: Experience with Federal Compliance frameworks, and requirements(e.g, Cloud SRG, FedRAMP, STIG Benchmarks, etc). Experience developing software & technical solutions that meet strict security & regulatory compliance requirements.
• 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 evolving project requirements. Ability to quickly grasp and apply new concepts and stay up-to-date with emerging trends in software engineering.
• Must be able to support work 3-4 days a week from the DC, SF, NYC, or STL office.