Jobs at Scale AI

As an Applied AI Engineer, you will build AI applications for public sector clients, create and evaluate datasets, and collaborate with teams to address challenges using AI solutions.

As a Software Engineer, you will develop backend services for AI applications, optimize cloud infrastructure, and manage production-level deployments.

The Machine Learning Engineer will design, train, deploy, and evaluate AI models to address public sector challenges, ensuring high-quality data training and evaluating systems.

Build and scale an enterprise Generative AI platform. Own large product areas across backend and frontend, develop reliable Python backend services, integrate LLMs, vector databases, and AI infrastructure, work with distributed systems and data pipelines, and ship features quickly while collaborating with product, ML, and infrastructure teams.

Build and operate core retrieval and knowledge representation systems for a generative AI platform: design RAG pipelines, embeddings, indexing, vector-store integrations, knowledge graphs/ontologies, evaluation frameworks, and production ML backend services while collaborating across product, ML, and infra teams and shipping enterprise-grade features.

Design, build, and maintain scalable, fault-tolerant serving platforms for LLMs. Integrate models for production and research, implement monitoring and observability, perform architecture reviews, and lead cross-functional end-to-end projects enabling LLM capability discovery and high-performance serving.

Design, build, and operate a secure, high-performance sandboxing platform and client library for code execution across containerized and virtualized environments. Ensure strong isolation, optimize latency and resource use, debug and reduce errors, respond to incidents, and drive roadmap and architecture reviews while partnering with internal users.

The Lead Counsel will expand Scale's Global Public Sector business, negotiate commercial agreements, manage public tenders, ensure compliance, and partner with various teams in the organization.

Manage engineering teams to deliver AI-driven applications, oversee product lifecycle, mentor engineers, and collaborate cross-functionally.

Lead design and development of core data storage, streaming, caching, and indexing platforms. Collaborate with cross-functional teams to deliver features, improve practices, mentor engineers, and present technical guidance to stakeholders while ensuring platform reliability and scalability.

Lead and own EMEA-specific assurance and certification programs (GCC, UK, EU), map controls, collect evidence, manage gaps and auditors, extend global certifications (SOC2, ISO), support customer assurance, legal and procurement compliance, and coordinate audits and regional regulatory engagement.

The Staff Technical Product Manager will own the product roadmap for Global Defense, design AI products, collaborate with engineers, and understand defense workflows to drive product outcomes.

Lead the Forward Deployed Engineering team, overseeing AI deployment and production excellence for major enterprise accounts while enhancing team capabilities and organizational standards.

As a Machine Learning Engineer, you'll train and deploy ML models for enterprise clients, work on deep learning solutions, and interface with product teams to enhance AI applications.

As a Solutions Engineer, you'll engage with customers to design AI solutions, deliver demos, and collaborate with teams, ensuring technical needs are met.

Design and implement identity infrastructure for authentication and authorization across enterprise systems. Build SSO, MFA, federated identity, and authorization systems (ReBAC/ABAC/RBAC). Implement governance policies for compliance (NIST, SOC2, ISO27001), and advise stakeholders on identity management best practices.

The Product Manager will lead the development of AI solutions, manage cross-functional teams, and drive product strategy, focusing on customer needs and enterprise applications of ML-powered products.

Lead a team of Product Managers to integrate Scale products into complex enterprise and government environments. Hire and mentor PMs, translate bespoke field deployments into scalable product strategy, partner with Sales/GTM and EPD, unblock high-priority deployments, and ensure the voice of the field informs roadmap decisions.

Lead strategic planning and execution for the Scale Generative AI Platform, owning technical scoping, architecture, and production launches. Coordinate cross-functional teams (platform engineering, Core ML, Research, Product), translate infrastructure metrics into roadmaps, mitigate deployment risks, define SLOs, drive developer velocity, and report adoption and reliability metrics to executive leadership to ensure scalable, secure, production-grade GenAI infrastructure.

Own end-to-end delivery of enterprise AI programs: manage timelines, risks, dependencies, and cross-functional integration. Translate technical complexity for engineering and executives, modernize agile workflows, and define program health metrics to drive adoption and scalable, reliable agentic solutions.