Role summary

Scale’s Operations Planning Team sits at the intersection of Engagement Management (EM), GenAI Delivery, GTM, and Growth Ops. The Planning TPM reduces friction between customer requirements and delivery by centralizing planning, standardizing reporting, and driving consistent process execution across accounts. As a TPM on Planning you will own program-level planning and systems workstreams that translate demand into reliable production plans, validate staffing, and ensure opportunities move through ingest accurately. This role combines program management, operational rigor, analytics literacy, and strong stakeholder management, with the goal of making account planning predictable, auditable and scalable.

This is a role designed to build deep account knowledge: each Planning TPM will ultimately be assigned to support 1–2 priority accounts to develop the context and relationships required to drive lasting operational improvements and more accurate planning and forecasting.

What you’ll own (key responsibilities)

Demand Forecasting

• Ensure project-level customer demand is captured accurately, consistently and at the right level of granularity.
• Own day-to-day monitoring and execution of Production Plan and Opportunity Forecast; act quickly on demand changes.
• Partner with Supply Ops to review the Production Plan weekly (PP, TCD, historical productive hours) and drive forecasting accuracy and adjustments.
• Surface forecast risks and coordinate tactical interventions through the Ops Planning leads.

Staffing & Resource Planning

• Create/validate staffing requests and communicate staffing changes to Delivery teams, STOs and EMs.
• Monitor account-level FTE budgets and employee spend; contribute to cost/benefit analysis of staffing vs. revenue.
• Stress-test staffing scenarios to provide early warnings on headcount risks and to inform hiring / reallocation decisions.
• Validate staffing tracking accuracy weekly; identify and correct discrepancies in project-level staffing data.

Opportunity Forecast & Ingest

• Ensure all revenue-generating opportunities are correctly logged in Opportunity Ingest (Linear) and that scoping is consistent.
• Act as the owner for opportunities as they move through the ingest workflow — expedite translation of demand signals into the forecast (Airtable / PP / OF).
• Run weekly checks to confirm Opportunity Forecast accuracy, and coordinate tactical scoping fixes when needed.

Account Intelligence & Systems Enablement

• Actively participate in core account meetings (ops, finance, GTM, delivery) as the Ops demand operational lead.
• Design, build and maintain scalable planning tools and account-level reporting artifacts (ramp planning sheets, account dashboards, account playbooks).
• Standardize and centralize information flow across customer ops pillars (demand forecasting, staffing, opportunity ingest).
• Drive systems enablement, process documentation (SOPs), and handoffs that reduce manual work and increase reliability.

With millions of diners, 60,000+ restaurant partners and 25+ years of experience, OpenTable, part of Booking Holdings, Inc. (NASDAQ: BKNG), is an industry leader with a passion for helping restaurants thrive. Our world-class technology empowers restaurants to focus on what matters most – their team, their guests, and their bottom line – while enabling diners to discover and book the perfect restaurant for every occasion. 

Every employee at OpenTable has a tangible impact on what we do and how we do it. You’ll also be part of a global team and its portfolio of metasearch brands. Hospitality is all about taking care of others, and it defines our culture.

The Role:

We’re looking for an accomplished and visionary Vice President, FP&A to lead, scale, and transform our global FP&A function. Reporting to the CFO, this leadership role requires a strategic partner to the CFO, executive team, and the extended leadership team, driving the overall financial strategy and performance management framework for OpenTable. This role requires exceptional executive presence, deep financial expertise, and a proven track record of leading high-performing teams.

In this role, you will:

• Set the strategic direction for the global financial planning process, including the annual budget, quarterly forecasts, and long-range planning, ensuring alignment with OpenTable’s corporate strategy and growth targets.
• Provide executive financial leadership and counsel to the CEO, CFO, and Executive Leadership Team on critical business decisions, performance drivers, and capital allocation strategies.
• Oversee and direct the preparation of sophisticated financial models and scenario analyses to evaluate new business ventures, M&A opportunities, and growth initiatives, ensuring robust data-driven decision-making.
• Lead the preparation and delivery of high-impact presentations and reporting to the Executive Leadership Team and the Board of Directors, offering clear visibility into financial performance, risks, and opportunities.
• Drive continuous improvement in financial systems, tools, and processes (e.g., Pigment, OneStream), establishing a best-in-class FP&A function for accuracy, efficiency, and scalability.
• Lead, mentor, and develop the entire FP&A team, fostering a culture of high performance, accountability, and continuous professional growth.
• Partner cross-functionally at the executive level (e.g., with Marketing, Product, Sales) to manage organizational resources and align financial objectives with company priorities.

Please apply if you have:

• 10-15+ years of progressive experience in FP&A, corporate finance, investment banking, or management consulting, including a minimum of 5 years leading a global or large-scale FP&A function.
• Exceptional executive-level presentation and verbal communication skills, with a proven ability to influence strategic outcomes across the organization.
• Deep expertise in financial modeling, scenario analysis, and advanced financial planning tools (e.g., Pigment, OneStream).
• Proven track record of building, mentoring, and scaling high-performing finance teams, driving accountability and superior results.
• Demonstrated ability to operate as a strategic business partner to C-level executives.
• A focus on accuracy and timely delivery, and are detail-oriented.
• Ability to prioritize and multitask in a fast-paced environment while meeting competing deadlines.
• Proactive, problem-solving approach, continuously looking for opportunities to improve processes.
• A high level of intellectual curiosity, a growth mindset, and a self-starter mentality.

Benefits and Perks

• Work from (almost) anywhere for up to 20 days per year
• Focus on mental health and well-being:
  • Company-paid therapy sessions through SpringHealth
  • Company-paid subscription to Headspace
• Annual company-wide week off a year - the whole team fully recharges (and returns without a pile-up of work!)
• Paid parental leave
• Generous paid vacation + time off for your birthday
• Paid volunteer time
• Focus on your career growth:
  • Development Dollars
  • Leadership development
  • Access to thousands of on-demand e-learnings
• Travel Discounts
• Employee Resource Groups
• Free lunch 5 days per week

There are a variety of factors that go into determining a salary range, including but not limited to external market benchmark data, geographic location, and years of experience sought/required. For this role based in our Norwalk, CT office, the base salary range is $260,000 to $280,000.

In addition to a competitive base salary, roles are eligible for additional compensation and benefits including: annual cash bonus, equity grant; health benefits; flexible spending account; retirement benefits; life insurance; paid time off (including PTO, paid sick leave, medical leave, bereavement leave, floating holidays and paid holidays); and parental leave and benefits.

Work Environment & Flexibility

At OpenTable, we pride ourselves on fostering a global and dynamic work environment. As a team member with us, you will benefit from a schedule tailored to accommodate a global workforce operating across multiple time zones. While the majority of your responsibilities may align with conventional business hours, there will be instances where you are expected to manage communications - via calls, Slack messages, or emails - outside of regular working hours to effectively collaborate with international colleagues, respond to restaurant partners, and/or address urgent matters. OpenTable will always abide by and consider local laws and regulations.

Inclusion

We’re committed to creating a workplace where everyone feels they belong and can thrive. We know the best ideas come when we bring different voices to the table, so we're building a team as dynamic as the diners and restaurants we serve—and fostering a culture where everyone feels welcome to be themselves.

If you need accommodations during the application or interview process, or on the job, we’re here to support you. Please reach out to your recruiter to request any accommodations.

With millions of diners, 60,000+ restaurant partners and 25+ years of experience, OpenTable, part of Booking Holdings, Inc. (NASDAQ: BKNG), is an industry leader with a passion for helping restaurants thrive. Our world-class technology empowers restaurants to focus on what matters most – their team, their guests, and their bottom line – while enabling diners to discover and book the perfect restaurant for every occasion. 

Every employee at OpenTable has a tangible impact on what we do and how we do it. You’ll also be part of a global team and its portfolio of metasearch brands. Hospitality is all about taking care of others, and it defines our culture.

The Role:

We’re looking for an accomplished and visionary Vice President, FP&A to lead, scale, and transform our global FP&A function. Reporting to the CFO, this leadership role requires a strategic partner to the CFO, executive team, and the extended leadership team, driving the overall financial strategy and performance management framework for OpenTable. This role requires exceptional executive presence, deep financial expertise, and a proven track record of leading high-performing teams.

In this role, you will:

• Set the strategic direction for the global financial planning process, including the annual budget, quarterly forecasts, and long-range planning, ensuring alignment with OpenTable’s corporate strategy and growth targets.
• Provide executive financial leadership and counsel to the CEO, CFO, and Executive Leadership Team on critical business decisions, performance drivers, and capital allocation strategies.
• Oversee and direct the preparation of sophisticated financial models and scenario analyses to evaluate new business ventures, M&A opportunities, and growth initiatives, ensuring robust data-driven decision-making.
• Lead the preparation and delivery of high-impact presentations and reporting to the Executive Leadership Team and the Board of Directors, offering clear visibility into financial performance, risks, and opportunities.
• Drive continuous improvement in financial systems, tools, and processes (e.g., Pigment, OneStream), establishing a best-in-class FP&A function for accuracy, efficiency, and scalability.
• Lead, mentor, and develop the entire FP&A team, fostering a culture of high performance, accountability, and continuous professional growth.
• Partner cross-functionally at the executive level (e.g., with Marketing, Product, Sales) to manage organizational resources and align financial objectives with company priorities.

Please apply if you have:

• 10-15+ years of progressive experience in FP&A, corporate finance, investment banking, or management consulting, including a minimum of 5 years leading a global or large-scale FP&A function.
• Exceptional executive-level presentation and verbal communication skills, with a proven ability to influence strategic outcomes across the organization.
• Deep expertise in financial modeling, scenario analysis, and advanced financial planning tools (e.g., Pigment, OneStream).
• Proven track record of building, mentoring, and scaling high-performing finance teams, driving accountability and superior results.
• Demonstrated ability to operate as a strategic business partner to C-level executives.
• A focus on accuracy and timely delivery, and are detail-oriented.
• Ability to prioritize and multitask in a fast-paced environment while meeting competing deadlines.
• Proactive, problem-solving approach, continuously looking for opportunities to improve processes.
• A high level of intellectual curiosity, a growth mindset, and a self-starter mentality.

Benefits and Perks

• Work from (almost) anywhere for up to 20 days per year
• Focus on mental health and well-being:
  • Company-paid therapy sessions through SpringHealth
  • Company-paid subscription to Headspace
• Annual company-wide week off a year - the whole team fully recharges (and returns without a pile-up of work!)
• Paid parental leave
• Generous paid vacation + time off for your birthday
• Paid volunteer time
• Focus on your career growth:
  • Development Dollars
  • Leadership development
  • Access to thousands of on-demand e-learnings
• Travel Discounts
• Employee Resource Groups
• Free lunch 5 days per week
• Beautiful office in the Empire State Building with lots of building amenities, such as a gym,  multi-purpose room, in-building Starbucks, and more. 

There are a variety of factors that go into determining a salary range, including but not limited to external market benchmark data, geographic location, and years of experience sought/required. For this role based in our New York City office, the base salary range is $260,000 to $280,000.

In addition to a competitive base salary, roles are eligible for additional compensation and benefits including: annual cash bonus, equity grant; health benefits; flexible spending account; retirement benefits; life insurance; paid time off (including PTO, paid sick leave, medical leave, bereavement leave, floating holidays and paid holidays); and parental leave and benefits.

Work Environment & Flexibility

At OpenTable, we pride ourselves on fostering a global and dynamic work environment. As a team member with us, you will benefit from a schedule tailored to accommodate a global workforce operating across multiple time zones. While the majority of your responsibilities may align with conventional business hours, there will be instances where you are expected to manage communications - via calls, Slack messages, or emails - outside of regular working hours to effectively collaborate with international colleagues, respond to restaurant partners, and/or address urgent matters. OpenTable will always abide by and consider local laws and regulations.

Inclusion

We’re committed to creating a workplace where everyone feels they belong and can thrive. We know the best ideas come when we bring different voices to the table, so we're building a team as dynamic as the diners and restaurants we serve—and fostering a culture where everyone feels welcome to be themselves.

If you need accommodations during the application or interview process, or on the job, we’re here to support you. Please reach out to your recruiter to request any accommodations.

Noom is on a mission to help people live better, longer. We’re a consumer-led digital health company, connecting people to content, coaching, community, and clinicians, to build lasting habits and live healthier lives. We’re a high-growth organization powered by science, technology, and world-class talent. When you join Noom, on any team, you’ll see the impact of your work on the world.

Our Clinical Research Team

Noom’s Clinical Research team generates rigorous, fit-for-purpose evidence that advances our mission across our portfolio of health offerings. We design and execute high-quality clinical and real-world research that supports medication-adjacent care and behavior-change interventions, ensuring our programs are backed by credible science and aligned with regulatory, commercial, and product needs. Our work strengthens Noom’s external scientific reputation while driving internal innovation and growth.

About the Role

As we continue to grow, we’re seeking a Clinical Research Scientist to design and execute rigorous clinical and real-world research across Noom’s health programs. This is a senior individual contributor role responsible for flexing across evidence standards—ranging from medication-adjacent clinical research to consumer-facing evidence development—while maintaining methodological rigor and scientific credibility. You will translate complex scientific findings into actionable insights that inform product strategy, claims development, and commercial decision-making.

You Will

• Design and execute clinical trials, pragmatic studies, and real-world evidence (RWE) initiatives across behavioral programs and digital interventions
• Adapt study designs, endpoints, and levels of rigor based on business and regulatory requirements
• Execute research across traditional site-based clinical settings and decentralized/virtual environments
• Develop statistical analysis plans and oversee analytic execution with senior scientific review
• Identify and mitigate methodological risks related to bias, confounding, and interpretability
• Ensure analytic outputs are defensible for peer review, internal decision-making, and appropriate claims development
• Serve as lead or contributing author on peer-reviewed publications and scientific communications
• Collaborate with academic investigators and external partners on study design, execution, and dissemination
• Translate research findings into clear, defensible insights tailored to product, marketing, medical, and legal/compliance stakeholders
• Align research designs with downstream business use cases while upholding scientific integrity
• Represent Noom’s research function in cross-functional and external forums
  
  

About You

If you’re interested in shaping the future of health by generating rigorous, credible evidence that drives trust and growth across innovative health programs, this role may be for you!

You Have

• PhD with advanced training in clinical research methodology, behavioral science, and statistical analysis
• 5–7+ years of related experience designing and executing rigorous clinical studies
• At least 3 years of experience in an academic research setting preferred
• At least 3 years of experience in a corporate or for-profit environment (e.g., digital health, healthcare technology, life sciences) supporting evidence generation and claims development for consumer-facing products preferred 
• Demonstrated understanding of the biological and behavioral mechanisms underlying GLP-1–based therapies
• Hands-on experience executing clinical trials, including traditional site-based and decentralized/virtual designs
• Strong statistical expertise and experience overseeing end-to-end analytic workflows
• Proven ability to connect study design and outcomes to claims development and business decision-making
• A publication track record demonstrating methodological rigor and analytical excellence
• Experience securing federal or peer-reviewed grant funding
• Experience collaborating with academic teams and commercial partners
• Demonstrated success interfacing with product and marketing teams to meet business objectives
• Working knowledge of relevant regulatory and compliance frameworks 

What Makes This Job Amazing

• The opportunity to shape evidence strategy across innovative, high-impact health programs
  A highly visible, senior IC role with meaningful influence on product and scientific strategy
• The chance to publish, collaborate externally, and elevate Noom’s scientific credibility
• The ability to translate rigorous science into real-world health impact at scale

What You'll Earn and Enjoy

• Pay that reflects your impact. Compensation benchmarked to the market and shaped by your impact and value.
• Investment in your future. A 401(k) with company match to help you build long-term financial security.
• Time to truly recharge. Paid holidays, generous time off, Summer Fridays, and a company-wide Summer Break week so the whole team can unplug together.
• Care that covers it all. Access to top-tier medical plans for you and your family, including a premium-free plan option, alongside dental, vision, and life insurance.
• Support for growing families. Paid parental leave to give you the time and flexibility to focus on what matters most.
• And more to help you thrive. Stock awards, performance-based bonus, and exclusive access to Noom’s products, so you can grow with us, win with us, and enjoy what we build.

The base salary range for this position is $145,000-$170,000. Actual compensation is determined by job-related factors, including experience, skills, qualifications, and location. 

This role is eligible for our NYC or Princeton office locations, operating on a hybrid schedule (2 days per week on-site).

More About Noom

Noom is a leading whole-person health platform on a mission to help people live better, longer. We combine personalized medication with the science of behavior change and psychology, to help people build lasting habits and live longer, healthier lives. With nationally-recognized, holistic programs spanning weight, diabetes prevention, GLP-1 support, menopause, longevity, and more, we serve millions through health plans, employers, and direct-to-consumer offerings. As a trailblazer in the world of health and wellness, Noom makes healthy living easy, fun, and deeply rewarding.

We’re more than a health tech company—we’re a movement. This belief extends to our culture: we empower our people to think big, act boldly, and take pride in their contributions to shaping the future of health. With a strong remote culture, as well as offices in NYC and Princeton, we’ve been named one of the Best Places to Work by Inc., Fortune, Glassdoor, and Quartz—including honors for technology and diversity.

Join us in shaping the future of health. Whether you're remote or in-office, you’ll be part of a passionate, mission-driven team working to make the world a healthier place—one habit at a time.

Noom is proud to be an Equal Opportunity Employer, and all applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, caste, national origin, physical or mental disability, protected veteran status, age, or any other characteristic protected by applicable law. Noom is committed to providing access, equal opportunity and reasonable accommodation for individuals with disabilities.

To help protect against potential hiring scams, please be aware that all email communications from the Noom Talent team and/or hiring managers will come only from an @noom.com email address. Please ignore any messaging or communication from other domains (e.g. @noom.team). Noom will never ask you for personal payment, require you to purchase equipment, conduct an interview process or messaging exchange via Microsoft Teams, or extend a job offer without the completion of a multi-step interview process featuring a combination of phone, Zoom, and in-person interviews, as well as references. If you are unsure about the validity of a Noom job posting on another website, we strongly encourage you to apply directly through our website.

Play a key role in how high-impact teams get built

Beast is growing quickly, and great recruiting at this scale depends on exceptional coordination, judgment, and care for the candidate experience. We’re looking for a Recruiting & Talent Operations Coordinator to own both the day-to-day logistics of hiring and the AI-powered systems that make our entire talent function faster and smarter.

This is not a traditional coordinator role. You’ll keep recruiting running smoothly at high speed while building the automations, dashboards, and AI-driven workflows that give our team a genuine edge. You’re highly organized, technically curious, and energized by fast-moving environments where both execution and innovation matter.

If you’ve already built workflows, automated repetitive tasks, or used AI to do more with less, and you can show us exactly how, this role is for you.

The Role

Reporting to the VP, Talent Acquisition & Technology, you’ll own the coordination and operational backbone of recruiting while engineering the AI-powered systems, dashboards, and automations that make our talent function smarter. You’ll sit at the center of recruiting, working across candidates, recruiters, and hiring managers, while surfacing insights through real-time data and continuously finding ways to reduce manual work without sacrificing the candidate experience.

What You’ll Do

Keep Recruiting Running Smoothly

• Coordinate interviews across multiple teams, time zones, and schedules.
• Manage candidate communications from first interview through offer stage.
• Ensure interviewers and candidates are prepared with the right information at the right time.
• Track candidates accurately through our ATS (Greenhouse) and recruiting tools.
• Partner with recruiters to manage interview loops, feedback timelines, and decision momentum.

AI-Driven Recruiting Operations

• Build and maintain AI-powered workflows that eliminate manual work across scheduling, candidate communication, follow-ups, and data entry.
• Identify every repetitive task in the recruiting process and ask: can this be automated? Then automate it.
• Use AI agents, prompt systems, and no-code/low-code platforms to replace manual coordination wherever possible.
• Document what you build, measure the impact, and keep iterating.

Recruiting Metrics & Dashboards

• Build and maintain real-time dashboards that track pipeline health, recruiter productivity, time-to-fill, interview conversion rates, and candidate experience scores.
• Surface insights that help recruiters and hiring managers make faster, better decisions.
• If a search is slowing down or a funnel is leaking, you’re the first to see it, and the first to flag it.

Deliver a Strong Candidate Experience

• Be a warm, responsive, and reliable point of contact for candidates.
• Use AI to personalize communication, reduce response times, and ensure no candidate ever falls through the cracks.
• Ensure every interaction, from first outreach to offer, feels fast, clear, and intentional.
• Represent Beast professionally and thoughtfully at every touchpoint.

Build Recruiting for Scale

• Identify opportunities to improve scheduling, tools, and processes.
• Build automations for scheduling, reminders, feedback collection, offer logistics, and onboarding handoffs.
• Create consistency and clarity as hiring volume increases.
• Be the person on the team who knows what’s possible and keeps pushing the boundary of it.

What You’ll Bring

AI is not optional here. You need to be able to show us what you’ve built.

• 1–3+ years of experience in recruiting coordination, HR operations, or a high-volume operational role.
• Hands-on experience building with AI tools such as GPT, Claude, Gemini, automation platforms, or equivalent. You use these daily, not occasionally.
• Demonstrated ability to build automations, prompt systems, agent workflows, dashboards, or tools that made a measurable difference in how work got done.
• Experience building dashboards or working with recruiting data such as time-to-fill, pipeline conversion, interviewer capacity, candidate NPS, or similar metrics.
• Strong organizational skills and attention to detail — high volume doesn’t mean things slip; your systems are tight enough that they don’t have to.
• Excellent written and verbal communication skills; fast, clear, and professional under pressure.
• Experience with ATS platforms (Greenhouse preferred) and scheduling or recruiting tools.
• Comfort working in a high-volume, fast-changing environment with the ability to juggle multiple priorities without losing accuracy or follow-through.
• Professional judgment, discretion, and a high bar for candidate experience.
• A builder’s mindset. You see inefficiency as a problem you’re responsible for solving.

The target total compensation ranges from $68,000 – $86,000 including a fixed annual salary of $62,000 – $78,000, an employee equity plan grant, bonus, plus comprehensive benefits.

Equity grants are issued in good faith, subject to company policies, board approval, and individual eligibility.

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

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)

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.

Scale GP (Scale Generative AI Platform) is an enterprise-grade AI platform that provides APIs for knowledge retrieval, inference, evaluation, and more. We are looking for a strong engineer to join our team and help us build and scale our core infrastructure in a fast-paced environment. 

The ideal candidate will have a strong understanding of software engineering principles and practices, as well as experience with large-scale distributed systems. You will implement solutions across multiple cloud providers (GCP, Azure, AWS) for customers in diverse, highly-regulated industries like healthcare, telecom, finance, and retail.

What You’ll Do:

• Architect multi-cloud systems and abstractions to allow the SGP platform to run on top of existing Cloud providers
• Implement custom integrations between Scale AI's platform and customer data environments (cloud platforms, data warehouses, internal APIs)
• Collaborate with platform, product teams and our customers directly to develop and implement innovative infrastructure that scales to meet evolving needs.
• Deliver experiments at a high velocity and level of quality to engage our customers
• Work across the entire product lifecycle from conceptualization through production
• Be able, and willing, to multi-task and learn new technologies quickly

What We’re Looking For:

• 4+ years of full-time engineering experience, post-graduation
• Experience scaling products at hyper growth startups
• Experience tinkering with or productizing LLMs, vector databases, and the other latest AI technologies
• Proficient in Python or Javascript/Typescript, and SQL
• Experience with Kubernetes
• Experience with major cloud providers (AWS, Azure, GCP)
• Excellent communication skills with the ability to explain technical concepts to both technical and non-technical audiences

Role:

Scale is at the forefront of the AI revolution, working across the US government, partners and allies around the world to unlock the potential of generative AI (GenAI).

We are seeking a product leader to join our team and play a pivotal role in building Agentic AI platforms to support national-level decisions, including for some of the nation’s most important national security challenges. The ideal candidate will have a strong understanding of product leadership, software engineering principles practices and deep experience with ML/AI application development, coupled with proven experience in managing complex projects with multiple stakeholder or AI-related projects within a government or highly regulated setting, emphasizing ethical AI deployment and robust risk management practices. 

This role requires a strategic leader adept at navigating the complexities of government GenAI projects, ensuring Scale’s public sector AI solution aligns with agency objectives and adheres to stringent security and compliance mandates. The product manager will be responsible for the entire lifecycle of the generative AI platform, including product design, cross-program execution, capability prioritization, stakeholder engagement with various government entities, defining and managing engineering scope, developing detailed project plans, and overseeing resource allocation and budget management. A key focus will be on ensuring that Scale’s public sector AI solution operates securely within controlled network environments, and is configured properly to support government workflows, specifically those that relate to national defense.

Some examples of GenAI applications we build are:

• Agentic warfare and scenario planning
• Indications and warnings integration for the protection of critical continental level assets
• Deep research capability that can help evaluate thousands of pages of classified information 
• Report generation for multiple customized report templates 
• Text2SQL intelligence applications to make analysts more efficient and embed a culture of data-driven decision-making

You will:

• Develop enterprise grade solutions that leverage cutting edge AI and AI agents to drive value for public sector customers 
• Work with executives at Scale and our customers to determine and execute the product strategy of the business.
• Own end-to-end product development by understanding customer pain points, defining product requirements, managing development, testing, and launches
• Lead cross-functional teams including engineering, product design, operations, marketing, go-to-market and finance.
• Develop a point of view and execute on turning the solutions we build into scalable software that we can commercialize across the industry 
• Maintain a Top Secret security clearance 

Ideally you'd have:

• Technical degree in computer science, engineering, or equivalent experience
• 4+ years of experience in building ML-powered and / or enterprise-facing products
• Strong understanding of generative AI technologies and their applications in public or large-scale private sector settings
• Experience operating in a fast-paced environment with high ambiguity
• Exceptional leadership, presentation, and communication skills with the ability to influence cross-functional teams
• Data literacy and experience with data analytics
• Prior military or government experience 
• Coding experience (e.g. Python)

Nice to haves:

• Experience building infrastructure and tooling to develop and support agentic applications.
• Experience working in startup environments building solutions for public sector / federal customers.
• Understanding of public / federal networks, infrastructure, and deployment constraints.
• TS/SCI Security Clearance

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.

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 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.

Staff Software Engineer, Full-Stack - Enterprise Gen AI

Scale GP (Scale Generative AI Platform) is an enterprise-grade AI platform providing APIs for knowledge retrieval, inference, evaluation, and more. We are looking for a frontend-focused full-stack engineer to help build AI-powered applications that redefine enterprise workflows and push the boundaries of interactive AI. This role is ideal for someone who thrives in a fast-paced environment, enjoys working on a diverse set of projects, and has a passion for crafting high-quality, intuitive user experiences.

At Scale, you'll work on a mix of cutting-edge customer-facing AI applications and internal SaaS products. Our engineering team powers projects like TIME’s Person of the Year AI experience (see it in action), where our AI technology helped shape one of the most iconic features in media. You'll also contribute to Scale’s GenAI Platform (SGP), a powerful system that enables businesses to build and deploy AI agents at scale. Whether it’s developing interactive AI assistants, enterprise-grade web applications, or refining our core SaaS platform, you’ll play a crucial role in shaping how AI integrates into real-world applications.

You Will:

• Build and enhance user-facing AI applications for major enterprise customers, including high-profile media and Fortune 500 companies
• Develop and refine features for Scale’s GenAI Platform, empowering businesses to build, deploy, and manage AI-driven agents
• Design, build, and optimize polished, high-performance UIs using Next.js, React, TypeScript, and Tailwind
• Work closely with product managers, designers, and AI/ML teams to create seamless, intuitive, and impactful user experiences
• Integrate frontend applications with backend services, working with APIs, authentication systems, and cloud-based infrastructure
• Ship features at a rapid pace while maintaining a high level of code quality, performance, and accessibility

Ideally, You Have:

• 5+ years of experience developing frontend or fullstack applications in a modern tech stack
• Strong proficiency in Next.js, React, TypeScript, and Tailwind, with an eye for building polished, user-friendly interfaces
• Experience working on high-visibility, customer-facing applications and making trade-offs between speed and quality in fast-paced environments
• A passion for AI and experience working on interactive AI applications, agent-based systems, or data-rich web platforms
• Familiarity with backend technologies such as FastAPI, PostgreSQL, GraphQL, and cloud infrastructure like AWS, Azure, or GCP
• A track record of collaborating cross-functionally with design, product, and ML teams to bring AI-powered applications to life

This role is a unique opportunity to shape the future of AI-powered user experiences, working on projects that impact millions of users while developing tools that empower businesses to deploy AI at scale. If you’re excited by the intersection of AI, frontend engineering, and product design, we’d love to hear from you.

The base salary range for this full-time position in our hub locations of San Francisco, New York, or Seattle is $248,400—$310,500 USD

. Compensation packages at Scale include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process. Scale employees are also granted Stock Options that are awarded upon board of director approval. You’ll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.

AI is becoming vitally important in every function of our society. At Scale, our mission is to accelerate the development of AI applications. For 8 years, Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including: generative AI, defense applications, and autonomous vehicles. With our recent Series F round, we’re accelerating the usage of frontier data and models by building complex agents for enterprises around the world through our Scale Generative Platform (SGP).

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

You will:

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

Ideally you'd have:

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

Nice to haves:

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

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.

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

Scale AI's Generative AI Data Engine powers the world's most advanced LLMs and generative models through world-class RLHF (Reinforcement Learning with Human Feedback), human data generation, model evaluation, safety, and alignment. The data they produced is described as some of the most important work for how humanity will interact with AI. 

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

You will:

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

Ideally you'd have:

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

Nice to haves:

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

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.

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

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

You will:

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

Ideally you'd have:

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

Software is eating the world, but AI is eating software. We live in unprecedented times – AI has the potential to exponentially augment human intelligence. Every person will have a personal tutor, coach, assistant, personal shopper, travel guide, and therapist throughout life. As the world adjusts to this new reality, leading platform companies are scrambling to build LLMs at billion scale, while large enterprises figure out how to add it to their products. To make them safe, aligned and actually useful, these models need human evaluation and reinforcement learning through human feedback (RLHF) during pre-training, fine-tuning, and production evaluations. This is the main innovation that’s enabled ChatGPT to get such a large headstart among competition.

At Scale, our products include the Generative AI Data Engine, SGP, Donovan, and others that power the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI.

At the foundation of these products is the Platform Engineering team. In this role, you will lead the design and development of core data storage, streaming, caching, and indexing platforms and underlying systems.  You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies.

You will:

• Drive the architecture, design, implementation, and reliability of our foundational data platforms and systems, working closely with stakeholders and internal customers to understand and refine requirements.
• Collaborate with cross-functional teams to define, design, and deliver new features.
• Proactively identify opportunities for, and driving improvements to, current programming practices, including process enhancements and tool upgrades.
• Present technical information to teams and stakeholders, providing guidance and insight on development processes and technologies.
• Provide technical leadership, including: upholding and upleveling engineering standards across the organization, mentoring junior engineers. 

Ideally you’d have:

• 8+ years of full-time engineering experience, post-graduation with specialties in back-end systems, specifically related to building large-scale data storage, streaming, and warehousing systems.
• Extensive experience in various database technologies (MongoDB, Postgres), streaming/processing solutions (Kinesis, Flink, Spark), indexing/caching (ElasticSearch, Redis), and various data query engines (Trino, Presto, Snowflake, etc.).
• Show a track record of mentoring and leading teams in successful projects.
• Possess excellent communication and collaboration skills, and the ability to translate complex technical concepts to non-technical stakeholders.
• Experience working fluently with standard containerization & deployment technologies like Kubernetes and various public cloud offerings.
• Extensive experience in software development and a deep understanding of distributed systems, cloud platforms and data systems.
• Experience driving cross functional collaboration and communication at an organizational or broader level. 

Nice to haves:

• Strong knowledge of software engineering best practices and CI/CD tooling (CircleCI).
• Experience with performance tuning and cost optimizations of cloud based data platforms. 
• Experience defining a data lifecycle strategy and designing/implementing tooling for data privacy (i.e. GDPR) needs.  
• Experience scaling products at hyper-growth startups.
• Excitement to work with AI technologies.

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:

• 7+ 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)

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.

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.

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 is looking for a Quality Lead to ensure top-tier data quality across our Generative AI programs. In this role, you will partner directly with Scale’s Delivery teams to ensure that the Quality Team’s core operation runs smoothly and that only high-quality data is delivered to our customers.

You will:

• Lead and develop teams of quality control auditors.
• Partner with delivery teams to interpret and improve customer requirements.
• Oversee day-to-day operations, including workload allocation and reporting insights.
• Establish and uphold scalable best practices.
• Drive initiatives that improve quality, efficiency, and customer satisfaction.

Ideally you'd have:

• A Bachelor’s degree in Computer Science, Engineering, Operations, or a related field.
• 2+ years improving operational/technical processes.
• Strong analytical and problem-solving skills (particularly in SQL and Google Sheets / Excel) with attention to detail.
• Experience building systems and processes
• A hands-on background in product management, software development, or top-tier management consulting.
• Proven experience taking initiative in cross-functional technical environments.

Nice to haves:

• Master’s degree in Computer Science, Engineering, Operations, or a related field.
• A hands-on background in quality assurance
• Experience in AI/ML services.
• Experience in a fast-growing, less-structured startup environment.
• Experience building teams from the ground up.

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.

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

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.

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'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

About Scale AI

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

Role Overview

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

This is a hands-on technical role that combines deep engineering expertise with customer-facing problem solving. You'll work directly with customer engineering teams to integrate AI into their critical workflows.

Key Responsibilities

Customer Integration & Deployment

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

AI Agent Development

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

Prompt Engineering & Optimization

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

Technical Leadership & Collaboration

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

Problem Solving & Innovation

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

Required Qualifications

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

Preferred Qualifications

Agent Development Wiz

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

Infrastructure Guru

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

Customer Product Whisperer

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

Sample Projects

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

Deep Research for Due Diligence

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

Churn Prediction

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

Data Extraction Voice Agent

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

Scale AI’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 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.

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 — AI Controls and Monitoring

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

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

As a Research Scientist focused on AI Controls and Monitoring, you will design methods, systems, and experiments to ensure that advanced AI models and agents remain aligned with intended goals, even in high-stakes or adversarial environments. For example, you might:

• Develop monitoring techniques and observability methods that track AI behavior in real time to identify and flag deviations, emergent capabilities, or anomalous outputs;
• Research mechanisms for layered control, including fail-safes, oversight protocols, and intervention methods that can halt or redirect AI systems when risks are detected;
• Design red-team simulations to probe weaknesses in oversight and control mechanisms, and build mitigations to close identified gaps;
• Collaborate with policymakers, engineers, and other researchers to establish standards and benchmarks for AI monitoring and escalation.

Ideally you’d have:

• Commitment to our mission of promoting safe, secure, and trustworthy AI deployments in the industry as frontier AI capabilities continue to advance.
• Practical experience conducting technical research collaboratively. You should be comfortable designing control and monitoring experiments for AI systems, building prototype systems, 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 with runtime monitoring, anomaly detection, or observability for ML systems.
• Familiarity with AI control or alignment research (e.g., scalable oversight, interpretability, debate).
• Experience with post-training and RL techniques such as RLHF, DPO, GRPO, and similar approaches.

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.

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

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.

AI is becoming vitally important in every function of our society. At Scale, our mission is to accelerate the development of AI applications. For 9 years, Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including generative AI, defense applications, and autonomous vehicles. With our recent investment from Meta, we are doubling down on building out state of the art post-training algorithms to reach the performance necessary for complex agents in enterprises around the world. 

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

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

You will: 

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

Ideally you’d have:

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

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.

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.

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.

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.

Role Summary

Scale is building the infrastructure layer for institutional intelligence — the compounding asset that makes the world's most consequential organizations more capable over time. The Chief of Staff to the VP of Product sits at the center of that work.

This is not a chief of staff role in the traditional sense. This person is not a scheduler, a note-taker, or a communications coordinator. They are an extension of the VP of Product, absorbing context across every workstream, making real prioritization calls, and operating at a level of organized precision that makes the rest of the function run faster.

The right person for this role wants to grow into product leadership and understands that the fastest path there is to operate at close range with someone doing the job. They will be in every room, on every decision, and responsible for ensuring that nothing falls through the cracks, including the principal.

What You'll Do

• Prepare the VP for every significant meeting, external or internal: customer briefings, executive reviews, board-adjacent discussions with the right level of context and the right framing.
• Represent the VP in internal workstreams where her presence isn't required but her perspective is. This means you actually have the perspective, not just her notes.
• Drive follow-through on decisions made in meetings: own the action items, chase closures, and surface blockers before they become problems.
• Build and maintain the operational infrastructure that keeps the product org coordinated. Rhythms, comms, templates, and shared context without it becoming process for its own sake.
• Engage directly with engineering leads, PMs, and go-to-market partners with enough technical and product fluency to move things forward, not just relay information.
• Move people without authority. You will regularly need engineers, PMs, GTM leads, and customers to do things that aren't in their immediate interest to prioritize. You get there by being trusted, well-framed, and well-timed, not by invoking the principal's name.

What We're Looking For

Must-Have Qualifications

• 10 years of experience in product management, technical program management, strategy, or a role with real operational ownership - not coordination.
• Demonstrated record of managing complexity: multiple parallel workstreams, competing stakeholder demands, and ambiguous ownership  and keeping all of it moving without dropping threads.
• Extreme organizational precision. Their systems are legible to others, not just themselves.
• Enough technical fluency to hold a real conversation with a platform engineer. Not deep coding, but genuine comprehension of how systems work: APIs, infrastructure, deployment, architecture at a conceptual level and curiosity to learn.
• The judgment to act on behalf of the principal. 
• Strong, precise written communication. First drafts should be clean. Recaps, briefs, and async updates should require minimal editing.

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.

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