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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.