About the Role

We’re hiring a Manager, Product Design to lead the design strategy and execution of Stitch Fix’s core experience, spanning how clients discover, request, receive, and engage with their Fixes, and how stylists deliver personalized styling at scale.

This role reports to the Head of Product Design and sits at the center of the business, with end-to-end ownership across both client and stylist journeys. You’ll define how these experiences evolve together, setting a clear product vision and driving alignment across cross-functional partners.
You’ll guide the work and raise the bar for craft and product thinking, while actively contributing to how key problems are framed and solved. A key part of this role is advancing how we use AI to enhance both sides of the experience. This includes integrating capabilities like Vision AI (our generative style visualization capability) into core journeys, while also enabling stylists with better tools.

You’ll partner closely with Product, Engineering, Algorithms, Merchandising, and Strategy to identify opportunities, prioritize investments, and bring cohesive, high-impact experiences to market. This role requires someone who can operate across strategy and execution, leading through others while also shaping critical work directly.

You're excited about this opportunity because you will…

• Shape the end-to-end experience: Define and drive design strategy across the full client journey, as well as the systems that support stylists
• Advance AI-powered experiences: Integrate AI into core journeys to enable more visual, personalized, and interactive experiences.
• Drive product evolution: Identify and deliver high-impact opportunities that move the experience forward, balancing foundational improvements with new ideas and approaches
• Lead and develop the team: Manage and coach designers, setting a high bar for craft, product thinking, and execution
• Influence cross-functional direction: Shape priorities, align roadmaps, and drive execution in close partnership with cross-functional leaders
   

We’re excited about you because…

• You have 8–12+ years designing consumer products, with 2–4+ years leading teams
• You have extensive experience owning complex, end-to-end product areas in consumer or marketplace environments
• You possess strong product thinking paired with excellent design craft
• You have the ability to define direction in ambiguous, high-impact problem spaces
• You have experience guiding teams while actively shaping work and outcomes
• You are a strong communicator with the ability to influence across teams and levels
• You have experience applying AI, ML and personalization to product experiences

Why you'll love working at Stitch Fix...

• We are a group of bright, kind people who are motivated by challenge. We value integrity, innovation and trust. You’ll bring these characteristics to life in everything you do at Stitch Fix.
• We cultivate a community of diverse perspectives— all voices are heard and valued.
• We are an innovative company and leverage our strengths in fashion and tech to disrupt the future of retail. 
• We win as a team, commit to our work, and celebrate grit together because we value strong relationships.
• We boldly create the future while keeping equity and sustainability at the center of all that we do. 
• We are the owners of our work and are energized by solving problems through a growth mindset lens. We think broadly and creatively through every situation to create meaningful impact.
• We offer comprehensive compensation packages and inclusive health and wellness benefits.

Responsibilities

• Support, administer, maintain IT systems supporting Quality and R&D, including Veeva Vault Quality, Clinical, RIM and Safety systems.
• Lead and oversee the migration of data and processes from legacy systems to Veeva (e.g., ZenQMS to Veeva Vault Quality) to ensure seamless transition, data integrity, and GxP compliance
• Partner with business leaders to understand their requirements and continuously improve user adoption and implement new systems, integrations, and GxP compliance initiatives
• Partner with Quality, Clinical, Regulatory, and Safety leaders to support business needs, implement roadmaps, identify, recommend solutions (e.g., Artificial Intelligence (AI)) to drive business value and accelerate innovation
• Work with Managed Service providers and internal IT teams for supporting and monitoring GxP-regulated systems to ensure high-quality service delivery
• Collaborate with CSV QA and compliance functions to validate and ensure alignment with regulatory requirements (e.g., GxP, HIPAA, GDPR)
• Establish governance, documentation, and change control procedures for GxP systems to ensure sustained compliance and operational excellence.
• Drive continuous improvement across the GxP systems landscape by assessing emerging technologies (e.g., AI) and optimizing workflows that support BridgeBio’s business strategy.

Where You’ll Work

• This is a local role and will require minimum 2 days in our San Francisco office. 

Who You Are

• Bachelor’s degree in information technology, Computer Science, Business Administration, or related field; advanced degree preferred
• 7+ years of progressive IT experience within biotech/pharma, including at least 5 years supporting Veeva Quality systems
• Demonstrated expertise in GxP Quality processes, including document lifecycle management, training assignment and compliance tracking, deviation, CAPA, and change control workflows, and inspection readiness. Ability to partner with Quality stakeholders to design, configure, and continuously improve Veeva Vault QualityDocs,
• QMS, and Training solutions in alignment with regulatory expectations (e.g., FDA, EMA) and company SOPs
• Hands-on experience administering and supporting Veeva Vault Quality systems including RIM, Safety and eTMF is strongly preferred
• Experience applying AI/ML and generative AI solutions within GxP environments to improve Quality operations, including use cases such as intelligent document authoring, metadata extraction, quality event trend analysis, and training effectiveness insights, with a strong focus on validation, auditability, data privacy, and integration with Veeva Vault platforms.
• Skilled in leading cross-functional collaboration across Quality, Clinical, Regulatory, and DSPV teams to ensure system alignment and process harmonization
• Experienced in vendor and Managed Service Provider oversight to ensure reliable, compliant, and high-quality system performance
• Strong communication, leadership, and stakeholder management skills with the ability to translate technical concepts into business outcomes

Who we are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies - from the world’s largest enterprises to the most ambitious startups - use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career.

About the team

We’re looking for an experienced regulatory licensing professional to manage our Audit & Regulatory Affairs team. In this role, you will coordinate with Stripe’s Legal, Financial Crimes, Finance, Accounting, Product, and Security teams, to (i) coordinate and submit regulatory license applications; (ii) manage license renewals and licence maintenance items; (iii) manage US regulatory exams and inquiries; and (iv) oversee other aspects of the team’s day-to-day activities, with a focus on licensing and exam activities related to digital assets.

Stripe’s mission is to increase the GDP of the internet. We build the most powerful and flexible tools for running an internet business. We handle billions of dollars each year and enable millions of users around the world to scale faster and more efficiently by building their businesses on Stripe. More than 80% of American adults bought something through Stripe in the last year.

Namely, Stripe’s North America regulatory affairs program plays a critical role in ensuring Stripe effectively manages its regulatory requirements and ongoing regulatory obligations for certain licensed US and Canadian entities. The role provides an excellent opportunity for a talented candidate to deploy their cross-functional licensing and regulatory exam management skills in a fast-paced and rigorous environment, enhance their regulatory risk management expertise, learn about digital assets, carve out opportunities to grow and develop, as well as lead a team of skilled and talented professionals. The successful candidate will gain wide ranging exposure to Stripe's diverse range of business lines, senior leadership, and the governance and workings of the organization.

The ideal candidate will be a self-starter who is exceptionally organized, thorough and detail-oriented, with a background in financial services, payments, digital assets, or other regulated sectors. In this role, you will get a chance to help build, enhance, mature and evolve our regulatory licensing and exam programs and be a key cross-functional partner. Stripe is both a technology company and a financial services company, and you will need to be comfortable in both worlds.

What you’ll do

The Audit & Regulatory Management Lead will help to ensure that all of the relevant components of the regulatory affairs program for licensed US and Canadian entities remain current and compliant, oversee managing and executing US regulatory examinations, and support our Compliance Audit Strategy, with the expectation to build a team who, in due time, will manage and drive exam oversight globally.

Responsibilities

• Coordinate responses to state regulatory inquiries, filings, forms, applications, renewals, surety bonds, and anything else required for license maintenance
• Assist in managing regulatory exams and inquiries, responding to regularly exam matters and monitoring the implementation and closure of any remediation items
• Stay abreast of regulatory changes, particularly with respect to digital assets, and how they impact regulatory affairs’ licensing and exam management program activities and responsibilities
• Establish and maintain relationships with internal and external partners and business units, relevant state and local agencies, licensing consultants, and outside counsel 
• Work proactively with Legal, Finance, Financial Crimes, Affiliate Officers, Product, and other key stakeholders on managing the regulatory affairs’s licensing and examination program 
• Support any end-to-end licensing, examination and related ad hoc inquiries as required in partnership with key stakeholders 
• Engage in special projects in support of the regulatory affairs program in North America

Who you are

We're looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.

Minimum requirements

• Bachelor’s degree in Finance, Political Science, Economics, or a related field 
• 10+ years experience in financial services, with significant experience in payments— familiarity with money transmitter statutes, NMLS, the BSA, and other areas of financial services, such as digital assets, lending, loan brokering and collections
• A history of professional achievement, including excellent academic credentials and success at a payments startup, financial institution, public sector organization, law enforcement agency, or top in-house legal department 
• Demonstrated familiarity with leveraging Generative AI and agentic workflows to automate preparing responses to routine questions and requests
• The ability to effectively and credibly communicate with senior executives, regulators and other stakeholders 
• Great interpersonal and critical thinking skills, good judgment, and the ability to work effectively with a wide variety of people inside and outside the company
• Robust communication skills

Who we are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies - from the world’s largest enterprises to the most ambitious startups - use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career.

About the team

The Finance & Strategy team is an integral thought partner to Stripe’s core functional leaders.  We bring understanding and predictability to Stripe’s bottom line financials.  We work cross functionally across many surfaces at Stripe and help steward Stripe’s resource investments to improve the durability of our long term financial performance.

What you’ll do

We’re hiring a seasoned finance leader to run Central GTM Finance & Strategy on the GTM F&S team. You will lead global planning, consolidation, metrics & analytics, and strategic initiatives that scale GTM finance operations. This role partners closely with Global Sales leadership to guide go-to-market strategy, improve forecasting accuracy, optimize investments, and accelerate enterprise growth as Stripe expands internationally.

Responsibilities

• Lead and develop a team of eight finance professionals supporting Global Sales; deliver insights across user-level performance, sales productivity, pipeline conversion, quota attainment, and strategic account planning to support recurring business reporting cadences.
• Provide finance leadership for global sales support functions including Solution Architecture, Customer Success, Renewals, and GTM Operations.
• Own global forecasting, planning, and budgeting for Sales; surface actionable insights that inform investment decisions and drive sales efficiency.
• Define and maintain key business metrics and KPIs to monitor health and proactively flag risks and opportunities.
• Use data-driven analysis to diagnose performance, recommend actions to accelerate revenue growth and margins, and optimize investments.
• Partner with Sales, Sales Operations & Strategy, and Marketing to evaluate ROI of GTM initiatives and customer acquisition strategies.
• Build dynamic financial and operating models to assess new sales motions, pricing changes, large enterprise deals, and regional expansion scenarios.
• Work with leadership to create long-range planning models that align team strategy with GTM and company priorities.
• Design, scale, and implement reporting and dashboards that track funnel metrics and primary investment drivers.
• Independently run complex SQL queries and perform hands-on analysis of raw data to validate models, uncover root causes, and produce actionable insights.
• Leverage AI and generative tools to speed analysis, automate repetitive tasks, surface insights, and synthesize recommendations.
• Drive process automation and data streamlining to improve reporting accuracy and decision velocity.
• Contribute to quarterly business reviews and long-range planning with scenario analysis and strategic recommendations.
• Translate complex financial and sales data into clear, concise narratives for executive audiences.

Who you are

You’re an analytical, execution-oriented finance leader with strong business acumen and a passion for GTM strategy. You thrive in fast-moving, ambiguous environments and balance strategic thinking with hands-on work. If you want to help Stripe scale its enterprise footprint and drive decisions through data, we want to hear from you.

Minimum requirements

• 10+ years in FP&A, Strategic Finance, or GTM Finance supporting enterprise sales teams.
• Proven ability to analyze pipeline health, forecast revenue, and model user and sales dynamics in complex B2B settings.
• Track record of partnering with senior GTM leaders and influencing decisions through financial insight.
• Strong financial modeling experience and familiarity with large, multi-variable planning tools.
• Proficiency in SQL to independently query and manipulate complex datasets.
• Analytical fluency at scale; comfortable working directly with large, complex datasets (not just financial models) to independently validate outputs, diagnose root causes, and drive conclusions in close partnership with Engineering, Data Science, and Analytics teams. 
• Ability to navigate ambiguous, evolving data environments; experience identifying non-obvious data pitfalls, understanding how data flows across systems, and building reliable analyses in settings where infrastructure and tooling are still maturing. 
• Minimum 3 years of people management experience with success leading high-performing finance teams.
• Excellent communication and presentation skills; ability to distill complex concepts into clear, actionable insights.
• Comfortable operating in fast-paced, ambiguous environments; able to balance strategy with tactical execution.

Preferred qualifications

• Experience working at a high-growth technology or financial services company
• Anaplan, Tableau or other equivalent application experience
• Advanced SQL skills
• Experience in data visualization and dashboarding

The Team

Our engineering team builds systems that interact with some of the most complex software  ever deployed in production. The team is composed of industry veterans that have built deep learning infrastructure, autonomous drones, ridesharing marketplaces, ad tech and much more. 

We are looking for a client-obsessed AI Solutions Engineer with entrepreneurial tendencies to join the good fight and help build out our Solutions Engineering org. You’ll be the trusted technical advisors for our customers, driving business value, offering advice, and growing accounts. You’ll accomplish this by leading customers to solutions oftentimes by teaching the product to new users or consulting on best practices. You must be ready for technical discussions with data scientists and engineers, then demonstrate the value of Arize in business discussions with directors and executives. The goal is to enable our customers to become successful and enthusiastic about Arize. While we are a remote-first company, the nature of this role requires candidates to be based in the San Francisco Bay area/PST time zone.

What You’ll Do

• Work closely with some of the most sophisticated ML / GenAI teams in the world.
  • You will act as a trusted advisor to our customers, while also building relationships with technical and business stakeholders.
• Advise on GenAI and ML best practices 
• Give ML and LLM product demos to technical and business stakeholders
• Run strategic business reviews for customers in partnership with our sales team
• Interface with our pre-sales engineering team to gather client goals and KPI’s.
• Partner with our product and engineering teams to help drive the product roadmap
• Spearhead new opportunities within existing accounts to help drive expansions.

What We’re Looking For

Note: Even if you do not check every single box, we still encourage you to apply! 

• Previous experience working as a Data Scientist, Machine Learning Engineer, or as an Engineer working with ML models or GenAI applications in production.
• Comfortable working in public Cloud environments (AWS, Azure, GCP)
• Knowledge of machine learning frameworks such as TensorFlow, PyTorch or Scikit-learn
• Knowledge of LLM / Agentic frameworks such as Llamaindex, LangGraph, and DSPy
• Understanding of ML/DS concepts, model evaluation strategies and lifecycle (feature generation, model training, model deployment, batch and real time scoring via REST APIs) and engineering considerations
• Understanding of GenAI concepts and application evaluation + development lifecycle  
• Proficiency in a programming language (Python, JS/TS, Java, Go, etc)
• Strong Communication Skills - Ability to simplify complex, technical concepts.
• A quick and self learner - undaunted by technical complexity of production ML deployments and welcome the challenge to learn about them and develop your own POV.

Bonus Points, But Not Required

• Previous engineering experience in:
  • Data Science
  • MLOps
  • ML Frameworks
  • LLM / Agentic frameworks
• Customer facing experience strongly preferred such as Solutions Architect, Implementation Specialist, Sales Engineer, Customer Success Engineer, Consultant, or Professional Service roles
• Prior experience working with applications deployed with Kubernetes
• Prior experience demoing technical products to both business and technical audiences

The estimated annual salary and variable compensation for this role is between $125,000 - $175,000, plus a competitive equity package. Actual compensation is determined based upon a variety of job related factors that may include: transferable work experience, skill sets, and qualifications. Total compensation also includes a comprehensive benefit package, including: medical, dental, vision, 401(k) plan, unlimited paid time off, generous parental leave plan, and others for mental and wellness support.

While we are a remote-first company, we have opened offices in New York City and the San Francisco Bay Area, as an option for those in those cities who wish to work in-person. For all other employees, there is a WFH monthly stipend to pay for co-working spaces.

About this role

As a Staff Machine Learning Platform Engineer, you will help design, improve, and operate a scalable ML platform to accelerate model training, deployment, and governance. You are the technical bridge between data science and production engineering.  You’ll be joining a small but deeply critical team that scales Faire’s ability to support tens of thousands of local businesses in a constantly narrowing retail landscape.

What You Will Do

• Design and operate ML infrastructure, including workspaces, clusters, jobs, and workflows
• Productionize ML workloads using Spark, Delta Lake, MLflow, and Databricks Workflows
• Teach data scientists how to utilize our ML platform to advance development from notebook to production for our most critical models
• Implement Unity Catalog for data governance, lineage, access control, and secure multi-tenant usage
• Build CI/CD pipelines for ML using Terraform and Git-based workflows (e.g., GitHub Actions)
• Optimize performance, reliability, and cost across training and inference workloads
• Configure Identity and Access Management (IAM) and Role Based Authentication Controls (RBAC) for sensitive data sets
• Establish observability for data quality, model performance, and platform health
• Build and maintain ML Platform technical documentation

What it takes

• 8+ years of experience building production ML or data platforms
• A degree (preferably graduate level) in Computer Science, Engineering, Statistics, or a related technical field
• Strong hands-on expertise with Databricks, Spark, Delta Lake, and MLflow.
• Proficiency in Python, SQL, and distributed systems concepts
• Experience with cloud platforms and infrastructure-as-code
• Solid understanding of MLOps best practices: CI/CD, monitoring, reproducibility, and security
• Experience supporting multiple ML teams in a shared platform environment
• Are an active owner of orphaned problems and are willing to assimilate whatever knowledge you’re missing to get the job done

Tech Stack

Faire uses a modern cloud based tech stack.  For this role, you’ll want to be proficient with the following:

Salary Range

Canada: the pay range for this role is $216,000 to $297,000 per year. 

This role will also be eligible for equity and benefits. Actual base pay will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location. The base pay range provided is subject to change and may be modified in the future.

Faire uses Artificial Intelligence (AI) to screen and select applicants for this position.

This job posting is for an existing vacancy.

Data at Brex

The Data organization develops insights, models, and data infrastructure for teams across Brex, including Sales, Marketing, Product, Engineering, and Operations. Our Data Scientists, Analysts, and Engineers work together to make data—and insights derived from data—a core asset across the company.

What you’ll do

As a senior Data Analyst (DA III), you will own the end-to-end analytics lifecycle for one or more business areas at Brex. You’ll go beyond building dashboards—you’ll frame the right questions, design rigorous analyses, apply statistical methods, and translate your findings into clear recommendations for leadership. You will also serve as a technical leader on the Data Analytics team, mentoring more junior analysts and helping define the standards and best practices that elevate the team’s work.

This role sits at the intersection of analytics, analytics engineering, and business strategy. You’ll work in a modern data stack environment and partner closely with Data Scientists, Data Engineers, and senior leaders across the organization.

Where you’ll work

This role will be based in our San Francisco office. We are a hybrid environment that combines the energy and connections of being in the office with the benefits and flexibility of working from home. We currently require a minimum of three coordinated days in the office per week, Monday, Wednesday and Thursday. As a perk, we also have up to four weeks per year of fully remote work!

Responsibilities

• Own the analytics lifecycle for assigned business areas: from problem framing and data sourcing through analysis, insight generation, and stakeholder presentation.
• Build and maintain dashboards and self-service reporting tools that enable business teams to independently track performance, identify risks, and make data-driven decisions.
• Write production-quality SQL and Python code to extract, transform, and analyze data at scale.
• Collaborate with Data Engineers and Data Scientists to develop and maintain analytical data models, improve data pipelines, and ensure data quality across the organization.
• Partner with leadership across Sales, Operations, Product, Finance, and other departments to identify high-impact analytical opportunities and deliver actionable recommendations.
• Mentor other data analysts and contribute to the development of team standards, documentation, code review practices, and analytical frameworks.
• Proactively identify gaps in data infrastructure, propose improvements, and contribute to the evolution of the team’s tooling and processes.

Requirements

• 5+ years of experience in data analytics, business intelligence, or a related quantitative role.
• 3+ years of experience partnering directly with Sales, Operations, Product, or equivalent business teams as an embedded analytics partner.
• Advanced SQL proficiency, including CTEs, window functions, performance optimization, and working across complex data models.
• Proficiency in Python for data analysis, automation, and modeling (Pandas, NumPy, scikit-learn, or similar).
• Experience with cloud data warehouses, particularly Snowflake (BigQuery and Databricks also valued).
• Hands-on experience with BI and data visualization tools (Looker, Tableau, Hex, or similar).
• Strong stakeholder management skills—proven ability to present complex technical findings to non-technical audiences.
• Experience with generative AI and LLM-based tools (Claude Code, Cursor, GitHub Copilot) to perform and accelerate analyses, automated reporting, and build self-service data tools.

Bonus points

• Demonstrated experience applying statistical methods to business problems (e.g., regression, classification, A/B testing).
• Experience with dbt for data modeling and transformation.
• Experience building and maintaining data pipelines using orchestration tools such as Airflow.
• Experience working with APIs for data ingestion and integration.
• Familiarity with version control systems (Git).
• Experience in fintech, financial services, or payments.
• Track record of leading cross-functional analytics projects from scoping through delivery.

Compensation

The expected salary range for this role is $114,192 - $142,740. However, the starting base pay will depend on a number of factors including the candidate’s location, skills, experience, market demands, and internal pay parity. Depending on the position offered, equity and other forms of compensation may be provided as part of a total compensation package.

Brex LLC is a wholly owned subsidiary of Capital One, N.A.

About Arize AI

AI is moving fast — but most teams are still flying blind once their models hit production. Arize builds the infrastructure that changes that: observability, evaluation, and iteration tools that give AI engineers real visibility into what their systems are actually doing.

We’re backed by $131M in funding — including the largest Series C ever raised in AI observability — with investors like Datadog, PagerDuty, and M12 (Microsoft’s venture fund). Our customers include Uber, Wayfair, and Tripadvisor. And Phoenix, our open-source observability tool, has become the go-to starting point for serious AI engineering teams worldwide.

We’re building the category. Now we need someone to help our customers tell that story.

The Role

Customer marketing at Arize isn’t a relationship management job — it’s a growth function. You’ll work directly with some of the most sophisticated AI engineering teams in the world, turning their wins into content, their voices into pipeline, and their communities into a compounding advantage for Arize.

You’ll sit at the intersection of product, sales, and customer success — owning the programs that help customers get more value from Arize while helping Arize grow through the customers we already have. That means building content, running programs, sourcing speakers, and creating campaigns — all with a technical audience in mind.

This is a high-visibility, high-ownership role on a lean team where what you build actually ships.

What You’ll Do

Customer Content & Storytelling

• Produce high-impact, customer-driven content across formats — video case studies, written success stories, social proof, and customer spotlights.
• Interview customers and translate technical wins into narratives that resonate with AI engineers and executive buyers alike.
• Build a library of proof points that sales, demand gen, and product can pull from.

Customer Reference Program

• Own and scale Arize’s customer reference program end-to-end — identifying advocates, managing relationships, and matching the right reference to the right opportunity.
• Partner with Sales to ensure reference coverage across segments, use cases, and industries.

Events & Speaker Sourcing

• Secure and prepare customer speakers for Arize events, webinars, conferences, and developer workshops.
• Support customer-facing events including meetups, workshops, and roundtables — from logistics to content.

Community & Advisory Programs

• Build and run programs like the Customer Advisory Board and power user groups that create tight feedback loops between customers and our product and GTM teams.
• Partner with Customer Success to amplify educational resources, best practices, and product adoption milestones.

Expansion & Adoption Campaigns

• Develop and execute campaigns that drive product adoption, increase engagement, and create upsell and expansion opportunities.
• Work cross-functionally with CS, Sales, and Product to identify expansion signals and turn them into pipeline.

What We’re Looking For

• 5+ years of experience in customer marketing, product marketing, or a closely related field — ideally at a developer tools, data infrastructure, or AI/ML company.
• Proven ability to identify customer stories and turn them into compelling content — you know how to find the narrative in a technical win.
• Experience running reference or advocacy programs and building scalable processes around them.
• Strong cross-functional collaborator — you’ve worked closely with Sales and Customer Success and understand how to support pipeline goals without losing the customer-first lens.
• Excellent written communication; comfortable writing for technical audiences without losing the thread for business stakeholders.
• Event and program management experience — you can run a webinar, coordinate a roundtable, and manage a speaker from ask to stage.
• Actively using AI in your day-to-day work — not just aware of it. You’re experimenting with AI tools to move faster, think more creatively, and do work that would have taken a team to do solo.

Nice to Have

• Background in or strong familiarity with AI/ML, LLMs, or data infrastructure.
• Experience with developer communities or open-source ecosystems.
• Familiarity with tools like Salesforce, HubSpot, or similar CRM/marketing automation platforms.
• Previous experience building CAB programs or structured executive engagement programs.

Why Arize

• We’re defining a category — and growing fast in it.
• Your work will have a direct impact on revenue, product, and community.
• You’ll work alongside some of the sharpest minds in AI infrastructure.
• Competitive salary, equity, and benefits.
• Hybrid work out of our San Francisco office.

Salary range $140,000-$175,000 dependent on experience

The Problem

Every large advertiser runs the same loop: strategist reviews performance data, decides what to test next, briefs a designer, waits for assets, hands them to a media buyer who builds campaigns across Meta and Google and TikTok, launches, monitors, repeats. The process is slow because creative production, campaign management, and performance analysis happen in three separate systems, and insights travel between them through decks, Slack threads, and weekly syncs.

Companies like Nike, Uber, and PepsiCo spend millions per month on digital ads and employ entire teams just to keep this loop turning. Most teams run 10 to 15 creative tests per month because every test requires manual work across multiple tools and teams. The result: most ad spend runs against stale creative, performance degrades from fatigue, and the gap between "what's working" and "what gets made next" is measured in weeks.

Why Agents Change This

Advertising is uniquely high-leverage for AI agents because nearly every step in the workflow is now automatable, and the steps compound:

• Research. Agents can continuously monitor competitor ad libraries, auto-classify creative by format, hook, and message, and surface positioning gaps. What used to require a strategist spending hours in Meta Ad Library happens in the background, always current.
• Creative production. Generative models can now produce ad-quality images and video. The constraint has shifted from "can AI make this" to "can AI make this on-brand and on-spec for each platform." That is a solvable engineering problem, not a research problem.
• Campaign structure. Building properly structured campaigns (naming conventions, audience splits, placement targeting, budget allocation) across five ad platforms is tedious, rules-based work. Agents can do it faster and more consistently than humans.
• Optimization. Detecting creative fatigue, reallocating budget toward winners, and knowing when to rotate in fresh variants is pattern recognition across structured data. Agents excel at exactly this.
• The compounding effect. When one agent handles the full chain (research, production, activation, analysis, iteration) as a single workflow, the cycle time collapses from weeks to hours. A team that runs 15 tests per month can run 50+, not because any individual step got faster, but because the coordination cost between steps drops to nearly zero.

Today: A performance marketing team testing new concepts on Meta and TikTok spends 2 to 3 weeks per cycle.

With agents: The marketing lead describes the objective. An agent analyzes recent performance, identifies the highest-value concepts to test, generates on-brand variants across formats, builds campaigns, launches after human approval, monitors results, detects fatigue, and queues replacements. Same team, 5x to 7x the testing volume, because the human bottleneck becomes strategy and judgment, not execution.

Why Hightouch, Why Now

Hightouch built the Agentic Marketing Platform: one system where AI agents own entire marketing workflows across lifecycle (email, SMS, push through Braze, Iterable, Salesforce, Adobe), advertising (creative production and activation across paid channels), and product experiences (real-time web and mobile experimentation). All three surfaces share the same agent infrastructure, brand and customer context, and warehouse-native data foundation. An insight the ads agent learns about creative performance can inform what the lifecycle agent sends. That shared context across every marketing surface is the product.

Ads is already live, and demand is surging. Enterprise customers are generating ad creative today with agents that analyze performance across Meta, Google, TikTok, LinkedIn, and Snapchat, produce briefs grounded in competitive research and brand guidelines, and generate ready-to-ship ad concepts. Early adoption has been strong: customers who start using it quickly expand usage across campaigns and teams, and inbound interest from enterprise prospects is accelerating. The foundation works. The opportunity is building it into a platform that captures the full advertising workflow.

What Hightouch has that no competitor can replicate:

• Agent orchestration. 25+ specialized agent skills for audience building, content generation, campaign analysis, and multi-step workflow coordination, all composable into end-to-end workflows.
• Content assembly with brand trust. Agents search existing asset libraries for reusable on-brand content before generating anything new. This is what makes output trustworthy enough for enterprises to ship without heavy review cycles.
• Marketing and brand context. A persistent layer connecting customer data, brand guidelines, creative assets, competitive intelligence, and performance history so agents operate with full business context, not generic prompts.
• Warehouse-native data foundation. 62,000 workspaces, a million data syncs per day, 300+ integrations. Customer data stays in the warehouse. No proprietary data store, no duplication, no lock-in.

The Role

You will lead the Agentic Ads Platform. The foundation exists (customers generating ads today), and the opportunity is turning it into the platform that closes the full advertising loop. Four major areas of work:

• Multi-model creative generation. Today the platform generates static images. The roadmap includes video generation, motion graphics, format adaptation, and multi-model orchestration (routing to the best model for each task). Building a creative generation pipeline that produces broadcast-quality output across formats is a hard, high-value problem.
• Marketing context and brand adherence. Making agents genuinely trustworthy for enterprise creative teams. Better context engineering so agents follow brand guidelines, business rules, legal requirements, and channel-specific policies without constant human correction. The gap between "AI-generated ad" and "ad our brand team would actually approve" needs to shrink dramatically.
• Platform depth across ad channels. Deep integrations with Meta, Google, TikTok, LinkedIn, Snapchat, and others. Not just launching ads, but understanding each platform's creative specs, optimization levers, and best practices so agents can automatically adapt creative for each channel, syndicate content across platforms, and optimize placement-level performance. Think: an agent that knows a 9:16 video with text-safe zones works differently on TikTok Reels vs. Instagram Stories and adjusts accordingly.
• Best-in-class agentic creation experience. The interaction model for how marketers work with agents to go from objective to live campaign. This means the conversational interface, the review and approval workflows, the feedback loops that help agents learn what "good" looks like for each brand, and the progressive autonomy controls that let teams start with full human approval and graduate to agent-led execution as trust builds.

Day to day, you will:

• Run deep customer discovery with performance marketing and creative teams at enterprise companies. Understand their workflows, pain points, and what would earn their trust.
• Define the product roadmap tied to revenue milestones. Sequence what to build, what to compose from existing systems, and what to partner on.
• Ship product. Work directly with engineering and design on tight cycles.
• Co-own pipeline and go-to-market. Join customer calls, shape competitive positioning, partner with CS on implementation.

High-visibility role working directly with founders and executive team.

What We're Looking For

• Zero-to-one track record. You have built products from nothing to meaningful revenue, ideally at a B2B SaaS company. The domain matters less than evidence you can find product-market fit under uncertainty.
• Technical depth. You can evaluate architectural tradeoffs, reason about things like multi-model orchestration and API integration design at the level of product decisions, and hold your own in debates with senior engineers.
• Commercial instinct. You think in terms of pipeline, conversion, and expansion. You build roadmaps that map to revenue targets.
• Speed. Small team, high autonomy, tight cycles. We use AI heavily in our own workflows and expect you to do the same.
• Cross-functional trust. This role spans engineering, design, sales, CS, and leadership. You drive clarity from ambiguity.

About the Role

Customer Studio is Hightouch’s second major product that provides a purpose-built no-code suite of features that enables anyone, regardless of their SQL experience, to activate data directly from their warehouse. The product has become an essential part of the day-to-day operations for marketing and growth teams to build and measure audiences and campaigns, and it also serves as part of the underlying infrastructure that powers our agentic marketing workflows. The team blends product and customer-first thinking with challenges at high data scale, helping us reimagine marketing in an AI-native world.

We’re looking to add a product-minded backend engineer to the team. The ideal candidate will be comfortable diving deep into backend and distributed systems and think holistically about architecture, scalability, maintainability, and reliability. We also are looking for someone with strong customer and product thinking and who feels comfortable writing and engaging with product specs.

Some of the problems we’ll be working on include:

• Data Warehouse Performance: We’re consistently pushing the limits of what data warehouses can handle in terms of speed, performance, and interactivity. We explore optimizations generally (e.g. optimizing queries, storing pre-computed state), as well as investigate warehouse-specific improvements.
• Analytics and Experimentation: How can Hightouch help customers build segments and decide what data they want to sync? How can we facilitate experimentation to downstream tools, including tracking the performance of different audiences?
• Real-time Audience Syncing: Our users are always interested in faster syncing and fresher data. As warehouses become more real-time and adopt technologies like CDC, we’re excited to explore real-time audience computation and syncing.
• Generative AI: We’re continuously working on making the user experience of acting on data more seamless, and are optimistic generative AI can enhance user workflows.

We are looking for talented, intellectually curious, and motivated individuals who are interested in tackling the problems above. This is a senior role, but we focus on impact and potential for growth more than years of experience. The salary range for this position is $180,000 - $320,000 USD per year, which is location independent in accordance with our remote-first policy. We also offer meaningful equity compensation in the form of ISO options, and offer early exercise and a 10 year post-termination exercise window.

Interview Process

Our interview process focuses on evaluating fit for the most important dimensions of the role: product sense, ability to architect backend and distributed systems, and alignment with Hightouch’s values. Notably, we don’t do any programming interviews as we believe they are low signal to noise and aren’t a good evaluation mechanism.

• Recruiter Screen [30m]: Introductory call with our recruiting team to get to know each other and see if the role could be a good mutual fit.
• System Design Screen [45m]: Designing a data processing feature end-to-end.
• Hiring Manager Interview [30m]: Chat with hiring manager about past experiences and future operating preferences to assess fit on company values and operating principles.
• System Design Interview [90m]: Work with the interviewer to architect a system at a conceptual level. The problem will be at a pretty high level - and have both product and customer requirements as well as technical.

#LI-DNI

About this role

As a Staff Machine Learning Platform Engineer, you will help design, improve, and operate a scalable ML platform to accelerate model training, deployment, and governance. You are the technical bridge between data science and production engineering.  You’ll be joining a small but deeply critical team that scales Faire’s ability to support tens of thousands of local businesses in a constantly narrowing retail landscape.

What You Will Do

• Design and operate ML infrastructure, including workspaces, clusters, jobs, and workflows
• Productionize ML workloads using Spark, Delta Lake, MLflow, and Databricks Workflows
• Teach data scientists how to utilize our ML platform to advance development from notebook to production for our most critical models
• Implement Unity Catalog for data governance, lineage, access control, and secure multi-tenant usage
• Build CI/CD pipelines for ML using Terraform and Git-based workflows (e.g., GitHub Actions)
• Optimize performance, reliability, and cost across training and inference workloads
• Configure Identity and Access Management (IAM) and Role Based Authentication Controls (RBAC) for sensitive data sets
• Establish observability for data quality, model performance, and platform health
• Build and maintain ML Platform technical documentation

What it takes

• 8+ years of experience building production ML or data platforms
• A degree (preferably graduate level) in Computer Science, Engineering, Statistics, or a related technical field
• Strong hands-on expertise with Databricks, Spark, Delta Lake, and MLflow.
• Proficiency in Python, SQL, and distributed systems concepts
• Experience with cloud platforms and infrastructure-as-code
• Solid understanding of MLOps best practices: CI/CD, monitoring, reproducibility, and security
• Experience supporting multiple ML teams in a shared platform environment
• Are an active owner of orphaned problems and are willing to assimilate whatever knowledge you’re missing to get the job done

Tech Stack

Faire uses a modern cloud based tech stack.  For this role, you’ll want to be proficient with the following:

Salary Range

San Francisco: the pay range for this role is $246,500 to $339,000 per year. 

This role will also be eligible for equity and benefits. Actual base pay will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location. The base pay range provided is subject to change and may be modified in the future.

Summary

The AI Intern will join the Technology team to design and implement intelligent solutions that make work smoother, smarter, and more efficient across the organization. Working closely with teams throughout the firm, this role will explore how generative AI and automation can streamline operations, surface insights, and improve efficiency across multiple departments.

This position is based in our San Francisco headquarters and requires 4+ days in office. The internship is full-time for approximately 12 weeks, with the option for extension. Exact schedule can be adjusted to accommodate the right candidate.

Responsibilities

Process Improvement

• Conduct workflow audits across departments to identify and document processes most ready for automation.
• Prototype automated processes and workflows to reduce manual effort and increase consistency.
• Partner with the Technology team and department stakeholders to integrate systems that support smoother cross-functional workflows.

AI Solutions & Tool Development

• Prototype an AI-assisted tool for a target department as a pilot project.
• Create visual dashboards integrating operational data and company metrics to generate actionable leadership insights.
• Contribute to the design of custom AI assistants for internal teams, supporting content structure, data organization, and prompt library development.
• Research, identify, and propose outside AI tools to assist with internal efficiency; assist with training and implementation.

Knowledge & Data Management

• Build and maintain AI learning resources and trainings for teams across the firm to support adoption of key AI tools.
• Own data management and documentation for assigned projects, including tracking milestones, decisions, and outcomes.
• Document project discussions and action items to promote accountability across AI-related workstreams.

Qualifications

• Current undergraduate or graduate student pursuing a degree in Computer Science, Information Systems, Data Analytics, Business, or a related field.
• Demonstrated curiosity about AI, automation, and digital transformation in the workplace.
• Familiarity with tools such as ChatGPT, Claude, Microsoft CoPilot, Zapier, Notion AI, or similar platforms.
• Strong analytical and communication skills with the ability to translate technical ideas into practical business solutions.
• Experience or coursework in Python, workflow automation, or dashboard design a plus.
• Highly organized, detail-oriented, and proactive in managing multiple projects.
• Thrives in a collaborative and fast-paced environment.

We provide reasonable accommodation to support individuals of all abilities in performing essential functions.

Compensation

• $20 - $30/ hour depending on experience
• Weekly lunch stipend

About The Role

The Senior Business Systems Analyst will be a key member of Snorkel’s Revenue Operations team. In this role, you will partner closely with Sales and Delivery stakeholders to understand operational needs and ensure our systems, especially Salesforce, are configured to support how our teams sell, deliver, and scale customer engagements.

You will also collaborate cross-functionally with Marketing, Finance, Analytics, Legal and Enablement teams to ensure new processes, system updates, and workflow improvements are aligned across the organization and do not negatively impact downstream systems or operational dependencies.

This is a hands-on role. The ideal candidate will not only gather and define business requirements but will also design and implement solutions across our GTM systems, including Salesforce and connected tools such as Gong, Outreach, Clay, and others, ensuring that systems capabilities align with operational needs.

What You’ll Do

• Partner with Sales and Delivery leadership to gather, document, and prioritize business requirements for operational systems and workflows.
• Translate business needs into scalable system designs and implement solutions directly in Salesforce, including objects, flows, validation rules, automation, and configuration updates.
• Collaborate with Revenue Operations and cross-functional teams (Marketing, Finance, Analytics, Delivery, and Supply) to ensure system changes and new processes align across teams and do not negatively impact downstream systems.
• Implement SOPs, governance frameworks, and system controls to improve Salesforce data hygiene and maintain Salesforce as a trusted source of truth.
• Evaluate existing operational processes and recommend system and workflow improvements that increase efficiency and scalability.
• Support the rollout of new system capabilities and enhancements across Salesforce and connected business systems.
• Ensure system changes are properly tested, documented, and communicated to stakeholders.
• Partner with Enablement to ensure systems and new processes are effectively adopted and consistently utilized across teams.
• Manage system change requests and collaborate with RevOps leadership on prioritization and rollout planning.

Required Qualifications

• 5+ years of experience in Business Systems Analysis, Revenue Operations, Sales Operations, or similar operational roles
• Strong experience gathering and translating business requirements into system solutions
• Salesforce Administrator certification with hands-on experience in Salesforce administration and configuration
• Familiarity with system integrations or workflow automation tools.
• Experience supporting Sales and Delivery operational workflows
• Strong documentation and process mapping skills
• Excellent stakeholder management and cross-functional communication skills
• Strong analytical and problem-solving abilities with high attention to detail
• Ability to manage multiple initiatives in a fast-moving environment

Bonus Points For

• Salesforce Advanced Administrator certification.
• Experience in B2B SaaS or AI/technology companies.

Location: Bay Area strongly preferred, Open to Remote.

The Opportunity

As an AI Solutions Manager, you’ll partner with some of the most innovative AI/ML teams in the world. You’ll play a pivotal role in driving adoption, shaping product use cases, and ensuring our customers succeed in leveraging AI to achieve real-world impact. This role offers a unique chance to grow alongside a leading AI company and gain deep insights into cutting-edge AI/ML applications. While we are a remote-first company, the nature of this role requires candidates to be based in the San Francisco Bay area/PST time zone.

The Team

Our engineering team builds systems that interact with some of the most complex software ever deployed in production. The team is composed of industry veterans that have built deep learning infrastructure, autonomous drones, ridesharing marketplaces, ad tech and much more. 

As an AI Solutions Manager, your work will directly contribute to our customers’ success in deploying impactful AI solutions, ensuring their models achieve measurable business outcomes. We are looking for a fast-paced, client-obsessed candidate with an entrepreneurial mindset to nurture, and grow our customers. You’ll be working with Arize customers to help them improve the AI they use across their organizations. You will be in charge of driving customer adoption and managing customers through their renewal cycles. You’ll accomplish this by running an effective account plan, identifying expansion opportunities with new teams, and building solutions to help achieve their goals. You’ll be involved in exciting and complex customer use cases and leverage your business acumen to navigate the intricacies.

What You’ll Do

• Build and deepen relationships with AI/ML users to foster adoption, uncover new use cases, and drive expanded usage across customer accounts. This includes regular touchpoints like weekly/bi-weekly calls and ongoing account management.
• Conduct discovery with customers to understand their goals, share the Arize vision, demonstrate product capabilities, and propose tailored solutions.
• Collaborate with technical teams, including Customer Success Engineering, to address complex customer needs, ensure smooth implementation, and advise on technical best practices.
• Run workshops and training sessions with customers during onboarding and new functionality
• Run QBRs to demonstrate account value, identify areas of opportunity, and strengthen customer partnerships.
• Proactively monitor product usage across your accounts to further gauge account health
• Work closely with Account Management and Executive teams to identify upsell opportunities and align on customer health strategies.
• Effectively relay customer feature requests to internal teams and advocate for customer needs.
• Ensure support teams are aligned with customer requests and priorities.

What We’re Looking For

• 3+ years of experience as a Customer Success Manager in SaaS.
• A self-starter mindset with the ability to thrive in limited process environments.
• Exceptional organizational skills with the ability to prioritize and manage multiple customer relationships effectively.
• Strong communication skills for articulating observations and fostering collaboration across teams.
• Proven ability to demo technical products and translate their value into tailored customer solutions.
• Thrives in fast-paced environments with a customer-first mindset and a focus on delivering measurable results.
• A strong team player who values collaboration and collective success.
• Bonus: Familiarity with AI/ML workflows or GenAI technologies.

The estimated annual salary and variable compensation for this role is between $140,000 to $175,000, plus a competitive equity package. Actual compensation is determined based upon a variety of job related factors that may include: transferable work experience, skill sets, and qualifications. Total compensation also includes a comprehensive benefit package, including: medical, dental, vision, 401(k) plan, unlimited paid time off, generous parental leave plan, and others for mental and wellness support.

While we are a remote-first company, we have opened offices in New York City and the San Francisco Bay Area, as an option for those in those cities who wish to work in-person. For all other employees, there is a WFH monthly stipend to pay for co-working spaces.

About the Role

We are hiring a Revenue Operations Lead to serve as a strategic operational partner to our GTM leadership as we scale to the next stage of growth. This role sits at the intersection of strategy, planning, and execution. You will partner closely with leaders across Sales, Solutions Engineering, Customer Success, and Delivery to translate company growth goals into operational plans, performance frameworks, and analytical insights that ensure our GTM motion is predictable, scalable, and data-driven. You will own and run the operating rhythm of the revenue organization, ensuring leaders have the visibility, discipline, and insights needed to execute against growth targets.

This role is ideal for someone who thrives in ambiguity, influences senior stakeholders with data-driven insights, and takes pride in building rigorous operational foundations for high-growth organizations. 

What You'll Do

Strategy & Planning:

• Lead key planning processes including territory design, segmentation, and quota allocation
• Build and maintain capacity and coverage models across sales and services teams
• Partner with Finance on headcount planning and revenue modeling
• Design and administer variable compensation plans, including incentive structures, accelerators, and SPIFFs that align sales behavior with company goals

Revenue Performance & Forecasting: 

• Own end-to-end forecasting and pipeline management across business units
• Ensure strong pipeline hygiene, deal progression, and inspection discipline
• Track performance against plan and drive initiatives with GTM leaders to address risks or gaps
• Partner with Finance and GTM leadership to maintain high-quality bookings and revenue forecasts

Business Insights & Decision Support: 

• Define and maintain the metrics, dashboards, and reporting frameworks used to run the business
• Surface trends across the customer lifecycle including pipeline generation, sales execution, delivery performance, and expansion
• Support executive decision-making by translating complex data into clear, actionable recommendations
• Establish standards for data quality, reporting consistency, and operational processes

Cross-Functional Collaboration: 

• Partner with Marketing, Finance, Sales, Customer Success, and Delivery to ensure GTM initiatives are well-coordinated and effectively executed
• Work with the Revenue Architecture and Data team to translate operational needs into scalable systems and workflows across CRM, forecasting, and reporting tools
• Lead through influence, driving adoption of processes, tools, and reporting standards across teams
• Reinforce a strong operating cadence and culture of accountability across the revenue organization

What We're Looking For

• 8-12+ years of experience in Revenue Operations, Sales Operations, or GTM Strategy at high-growth technology companies
• Experience supporting enterprise sales organizations and services delivery models
• Strong expertise in forecasting, pipeline management, capacity modeling, and designing sales incentive and variable compensation programs
• Excellent communication skills, with the ability to influence senior GTM leaders through clear data-driven insights
• Comfort operating in a fast-paced, ambiguous environment, balancing strategy with hands-on execution
  
  

Scale GP (Scale Generative AI Platform) is an enterprise-grade Generative AI platform providing APIs for knowledge retrieval, inference, evaluation, and more. We are seeking a strong Senior Full-Stack Engineer to help us build, scale, and refine our rapidly growing product. The ideal candidate is deeply grounded in software engineering best practices and experienced in developing and scaling modern web applications end-to-end. You will work across the stack—from React/TypeScript frontends to Python-based backends—while integrating with LLMs and machine learning systems.

You will solve complex challenges in scalability, reliability, and product experience while owning significant product areas in a fast-paced environment.

What You’ll Do

• Own major full-stack product areas, driving features from design through production deployment.
  
  
• Build modern frontend experiences using React and TypeScript, ensuring performance, usability, and responsiveness.
  
  
• Develop reliable backend services in Python, working with distributed systems, data pipelines, and ML/LLM components.
  
  
• Integrate with LLMs, vector databases, and AI infrastructure to power intelligent product experiences.
  
  
• Deliver experiments and new features quickly, maintaining high quality and tight feedback loops with customers.
  
  
• Collaborate across product, ML, and infrastructure teams to shape the direction of Scale GP.
  
  
• Adapt quickly—learning new technologies, frameworks, and tools as needed across the stack.
  
  

Ideal Experience

• 5+ years of full-time engineering experience, post-graduation.
  
  
• Strong experience developing full-stack applications using React, TypeScript, and Python.
  
  
• Experience scaling or shipping products at high-growth startups.
  
  
• Familiarity with LLMs, vector databases, embeddings, or other modern AI tooling (tinkering or production experience welcome).
  
  
• Proficiency with SQL and modern API development.
  
  
• Experience with Kubernetes, containerization, and microservice architectures.
  
  
• Experience working with at least one major cloud provider (AWS, GCP, or Azure).

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

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

You will:

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

Ideally you'd have:

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

About Scale

At Scale AI, our mission is to accelerate the development of AI applications. For 8 years, Scale has been the leading AI data foundry, fueling the most exciting advancements in AI, including generative AI, defense applications, and autonomous vehicles. With our recent Series F round, we’re amplifying access to high-quality data to drive progress toward Artificial General Intelligence (AGI). Building on our history of model evaluation with enterprise and government customers, we are expanding our capabilities to set new standards for both public and private evaluations.

About This Role

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

Ideally, you’d have:

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

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

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

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

Nice to have:

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

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

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

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

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

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

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 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.

Example Projects:

• Ship tools to accelerate the growth of new qualified contributors on Scale’s labeling platform
• Build methodical fraud-detection systems to remove bad actors and keep Scale’s contributor base safe and trusted. 
• Use models to estimate the quality of tasks and labelers, and guarantee quality on requests at large scale.
• Devise advanced matching algorithms to match labelers to customers for optimal turnaround and accuracy.
• Build methods to automatically measure, train, and optimally match labelers to tasks based on performance
• Create optimized and efficient UI/UX tooling, in combination with ML algorithms, for 100k+ labelers to complete billions of complex tasks
• Develop new AI infrastructure products to visualize, query, and explore Scale data
• Create a customer service RAG application that handles 1000s of questions a day
• Integrate a cutting-edge ML model that predicts churn with a customer's retention system

Requirements:

• A graduation date in Fall 2025 or Spring 2026 with a Bachelor’s degree (or equivalent) in a relevant field (Computer Science, EECS, Computer Engineering, Statistics) 
• Product engineering experience such as building web apps full-stack, integrating with relevant APIs and services, talking to customers, figuring out ‘what’ to build and then iterating
• Previous Product/Software Engineering Internship experience 
• Track record of shipping high-quality products and features at scale
• Experience building systems that process large volumes of data
• Experience with Python, Typescript, React, and/or MongoDB

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

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

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

You will: 

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

Ideally you’d have:

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

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

You will:

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

Ideally you’d have:

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

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

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.

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

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.

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 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

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.

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

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

At the foundation of these products is the Platform Engineering team. As a Staff Software Engineer, you will define and drive both the architectural roadmap and implementation of core platforms and software systems. You will be responsible for providing high-level vision and driving adoption across the engineering org for orchestration, data abstraction, data pipelines, identity & access management, and underlying cloud infrastructure.  You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies.

Impact and Responsibilities:

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

Ideally you’d have:

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

Nice to haves:

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

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.

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.

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.

About Scale

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

About Data Engine

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

Our Approach 

As part of the interview process, you’ll be considered for opportunities across several teams within the GenAI Engineering organization, based on your interests, expertise, and business needs. Potential team placements include Allocation, Growth, Frontier Data, Trust & Safety, Pay, Operator, or Tasking Experience. Together, these teams power Scale’s AI data operations - from building high-impact datasets that push the boundaries of LLM capabilities, to optimizing contributor onboarding and incentives, to safeguarding data integrity through advanced trust, safety, and security measures. They work at the intersection of ML, operations, and analytics to ensure we deliver the highest-quality data at scale.

Responsibilities:

• Design, build, and maintain robust, scalable systems across the full stack, including front-end, back-end, and infrastructure layers
• Implement high-impact features using modern technologies such as TypeScript, React, Node.js, MongoDB, Elasticsearch, and Temporal
• Collaborate closely with internal operators (your users are your neighbors) to identify bottlenecks and ship fast, pragmatic solutions
• Own core systems critical to our contributor platform, with direct impact on Scale’s GenAI data pipeline and business outcomes
• Architect and scale infrastructure capable of handling millions of tasks per week with high reliability and low latency
• Partner cross-functionally with ML teams, Forward Deployed Engineers, and Product to ensure data quality and operational excellence
• Contribute to a strong engineering culture while setting best practices for teammates through mentorship, code reviews, and process improvements

Requirements:

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

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

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

You will:

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

Ideally you’d have:

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

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

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

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

You will: 

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

Ideally you’d have:

• At least 1-3 years of LLM training in a production environment
• Passionate about system optimization
• Experience with post-training methods like RLHF/RLVR and related algorithms like PPO/GRPO etc.
• Ability to demonstrate know-how on how to operate the architecture of the modern GPU cluster
• Experience with multi-node LLM training and inference
• Strong software engineering skills, proficient in frameworks and tools such as CUDA, Pytorch, transformers, flash attention, etc. 
• Strong written and verbal communication skills to operate in a cross functional team environment.
• PhD or Masters in Computer Science or a related field

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.

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

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.

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

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

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

You will:

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

Ideally, you'd have:

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

Nice to haves:

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

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

Job Description: Distinguished Engineer, Enterprise AI 

About Scale AI

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

The Role

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

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

Responsibilities

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

Qualifications

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

Culture & Impact

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

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

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

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

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

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

You will:

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

Ideally you'd have:

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

Nice to haves:

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

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

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

You will:

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

Ideally you'd have:

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

Nice to haves:

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

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.

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

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

You will:

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

Ideally You’d Have:

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

Nice to Haves:

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

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

You will:

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

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

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

Must haves:

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

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

About Data Engine

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

About our AgentOps team: 

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

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

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

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

Responsibilities:

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

Requirements:

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

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

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

This is a 0→1 build team. We’re looking for a sharp, product-minded Senior Engineer who thrives in ambiguity, moves quickly, and enjoys building new systems from scratch alongside customers and cross-functional partners. You’ll work closely with product, forward-deployed engineers, data scientists, and applied AI teams to turn real-world problems into scalable, production solutions.

If you like shipping fast, owning outcomes, and working across the stack—from polished frontends to distributed backends to LLM integrations—this role is for you.

What You’ll Do

• Own major full-stack product areas, driving features from concept and design through production deployment
• Build intuitive, high-performance frontend experiences using React + TypeScript
• Develop reliable backend services in Python, working with distributed systems, data pipelines, and AI/ML infrastructure
• Integrate LLMs, vector databases, and agentic frameworks to power intelligent workflows and decision-making systems
• Ship quickly through tight experimentation loops while maintaining high quality and reliability
• Help define the technical direction and architecture of a brand-new team and product surface
• Adapt across the stack and learn new tools as needed to solve real problems end-to-end

Ideal Experience

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

What We Value

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

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

Scale AI’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.