Responsibilities
- Own major platform areas and drive components from design through production deployment.
- Build knowledge representation systems, including ontologies and knowledge graphs, for structured reasoning over enterprise data.
- Design and implement RAG pipelines covering chunking, embedding, indexing, retrieval, and reranking.
- Integrate retrieval and ML components with enterprise data sources, vector databases, APIs, and services.
- Develop context retrieval systems that balance recall, precision, latency, and cost.
- Build evaluation frameworks, datasets, and metrics for retrieval quality, context relevance, and end-to-end agent performance.
- Build reliable backend services and data pipelines supporting ML and LLM components in production.
- Deliver experiments and capabilities quickly while maintaining quality and customer feedback loops.
- Collaborate with product, ML, and infrastructure teams to shape the platform.
Requirements
- 5+ years of experience building and deploying machine learning or AI systems for real-world production use cases.
- Master’s or PhD in Computer Science, Machine Learning, AI, or equivalent practical experience.
- Deep hands-on understanding of retrieval systems, RAG, embeddings, vector indexing, and knowledge representation.
- Experience with knowledge representation, semantic search, or agentic systems.
- Proficiency in Python and production-quality, testable, maintainable software development.
- Experience scaling or shipping products at high-growth startups.
- Ability to balance research-driven approaches with pragmatic product constraints.
- Strong communication skills and comfort working in customer-facing or cross-functional environments.
Tech Stack
Categories
About Scale AI
Scale’s mission is to develop reliable AI systems for the world’s most important decisions. We provide the high-quality data and full-stack technologies that power the world’s leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. The Scale Generative AI Platform allows customers to build, evaluate, and control advanced AI agents and applications that continuously improve. The Scale Data Engine provides the technology to collect, curate, and annotate high-quality datasets. Through our Scale Labs, we test models with rigorous benchmarks and novel research to ensure breakthroughs translate into systems people can trust. Scale powers the most advanced LLMs and generative models in the world through RLHF, data generation and model evaluation. We work with industry leaders like Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force.