Jobs at Scale AI

This role involves developing AI applications, focusing on LLMs and agent frameworks, and requires research skills in ML with experience in data strategy.

As a Senior Software Engineer, you'll scale the Scale Generative AI Platform, owning product areas, working across multiple tech stacks, and solving engineering challenges.

This role involves building and optimizing ML systems and frameworks, collaborating with teams to enhance research and development in ML models.

Lead AI policy development, regulatory engagement, government relations, and external advocacy in the US and globally. Develop policy positions, respond to rulemakings, advise executives, monitor regulatory changes, build stakeholder relationships, and represent the company with governments, trade associations, standards organizations, and think tanks. Collaborate cross-functionally and advance AI policy research and thought leadership.

Lead the architecture and implementation of AI-assisted developer tooling, local development workflows, build and test systems, CI/CD platforms, and deployment processes. Mentor software engineers, establish engineering best practices and governance, configure AI agents and MCP servers, improve development tools and languages, and communicate technical guidance to stakeholders.

Own growth programs that attract, onboard, and retain domain experts for AI systems. Set strategy, manage execution and teams, build expert pipelines, automate sourcing and onboarding with AI, analyze performance, run experiments, and scale successful processes into repeatable playbooks. The role requires strong ownership, data-driven decision-making, program operations experience, team leadership, and hands-on automation skills.

Leads quality control for high-impact generative AI programs, managing and developing quality specialists, translating customer requirements into measurable standards, and operating quality systems. Responsibilities include workforce planning, reporting, productivity measurement, defect analysis, root-cause investigation, cross-functional accountability, and development of scalable, technology-enabled quality operations.

Lead architecture, development, reliability, and improvement of foundational data platforms covering storage, streaming, caching, indexing, and warehousing. Collaborate with cross-functional stakeholders, deliver platform features, improve engineering practices and tooling, present technical guidance, and mentor engineers. The role requires extensive distributed systems, cloud, database, containerization, deployment, and large-scale data platform experience, with emphasis on technical leadership and organizational collaboration.

Own and build Scale’s partner marketing function, driving pipeline through AWS, Google Cloud, Microsoft, and other strategic partners. Develop co-sell motions, account mapping, marketplace programs, joint campaigns, partner funding strategies, and executive reporting. Manage partner marketing budgets against pipeline outcomes, improve lead handoffs and opportunity conversion, and collaborate with Partnerships, Sales, Product Marketing, and Operations to package and promote joint offerings.

Leads product marketing for Scale’s enterprise applications business, with a focus on financial services and launching new verticals. Develops positioning, messaging, sales plays, enablement, marketing assets, integrated campaigns, ABM programs, event strategies, and go-to-market playbooks. Partners with sales, product, engineering, growth marketing, field marketing, and communications teams. Measures pipeline and program impact while influencing executive and cross-functional stakeholders.

As an Engagement Management Lead, you'll manage strategic customer relationships, oversee project delivery, and ensure quality outcomes while navigating complex customer dynamics.

Design, build, and maintain foundational platform systems and cloud infrastructure supporting Scale's AI data and RLHF products. Collaborate with cross-functional teams to define features, improve engineering practices, and drive platform reliability, deployment, and CI/CD workflows.

Conduct cutting-edge machine learning research involving frontier models, reinforcement learning, post-training, scalable oversight, synthetic data, safety, evaluation, and alignment. Interns develop and improve production ML systems, research new methods, conduct experiments, and may publish or ship work with mentorship from researchers and collaboration across industry and academia.

Design responsive, accessible, high-performing web experiences for Scale's digital properties, primarily scale.com. Create wireframes, prototypes, high-fidelity mockups, reusable design systems, components, and page templates. Partner with engineers and cross-functional stakeholders to communicate design intent, review implementations, evolve the brand, and improve user experiences. Explore emerging AI tools, interaction patterns, analytics, and experimentation to deliver innovative, scalable digital experiences.

Design and develop shared platform systems, foundational data platforms, cloud infrastructure, orchestration, and software delivery tooling. Partner with stakeholders and cross-functional teams to define and deliver features, improve engineering practices, and communicate technical concepts. The role requires expertise in backend systems, distributed systems, public cloud, containerization, databases, orchestration, and CI/CD, with opportunities to support AI-focused products.

Lead the architecture, development, and operation of a reliable orchestration platform for distributed workflows. Build workflow primitives, APIs, and infrastructure supporting scheduling, retries, state management, observability, security, scalability, and developer experience. Partner with cross-functional teams, establish engineering standards, and drive technically complex projects from design through production operation.

Own outbound prospecting, customer education, discovery, and Stage 2 qualification for enterprise AI opportunities. Generate and qualify pipeline, explain AI capabilities and workflows, develop customer narratives, coordinate with Solutions Engineering, Marketing, and GTM Strategy, and transition qualified opportunities to Account Executives. Maintain CRM hygiene and pipeline visibility while building expertise in enterprise AI deployment patterns and customer use cases.

Lead account-based marketing programs for strategic enterprise accounts across healthcare, financial and professional services, and consumer verticals. Own ABM strategy, multichannel campaign execution, account planning, stakeholder engagement, KPI reporting, pipeline attribution, and repeatable playbook development. Partner with enterprise sales, growth marketing, content, product marketing, and field teams while managing creative production and fulfillment partners.

Lead initiatives to drive revenue and growth in Generative AI, collaborating with teams and developing strategies aligned with market needs.

Lead and grow the enterprise product design team: set design direction, hire and develop designers, drive end-to-end design execution, raise craft standards, contribute to the design system, root decisions in user research, and define human-agent interaction patterns for AI workflows.