Air
Lead Data Scientist - Knowledge Retrieval
Pittsburgh, Pennsylvania, United States · Full-time
No sponsorshipDetected 11 days ago
ReactVector DatabasesAWSGCPAzureCloud PlatformsMachine LearningData EngineeringData ScienceNLPLLMsRAGAgentic AIMLOpsA/B TestingExcelResearchLeadershipCommunicationProblem SolvingMentoringOrganizational Skills
About the role
- Company Description Air is the leader in Enterprise Readiness.
- Today, a dangerous Readiness Gap exists between what the front line needs and what is delivered.
- By revealing true capacity, exposing real constraints, coordinating resources, and executing at the speed of operational demands, the front line gets what it needs to succeed.
Requirements
- U.S. Citizenship is required
- Expertise in designing and implementing Retrieval-Augmented Generation (RAG) architectures and complex indexing strategies for proprietary, large-scale, heterogeneous datasets.
- Expertise in fine-tuning multi modal embedding models
- Deep knowledge of and practical experience with ranking and reranking models, including multi-tower, bi-encoder and cross-encoder architectures, specifically within the context of search and knowledge retrieval systems.
- Experience with MLOps practices, including deployment, monitoring, and management of large-scale models in cloud environments (e.g., GCP, AWS, Azure).
- Track record of successfully transitioning AI research prototypes into robust, production-grade enterprise solutions
- Required Skills:
- Expertise in designing and implementing Retrieval-Augmented Generation (RAG) architectures and complex indexing strategies for proprietary, large-scale, heterogeneous datasets. Expertise in fine-tuning multi modal embedding models
- Proven ability to leverage state-of-the-art LLMs, multi-modal embedding models, vector databases, and knowledge graph systems to build production-ready knowledge retrieval, conversational AI search, and Deep Research systems.
- Practical experience building hybrid knowledge retrieval systems that combine advanced techniques like embedding models, knowledge graphs, and traditional methods (e.g., BM25), utilizing novel paradigms such as GraphRAG, RAG-RL, and other advanced retrieval strategies.
- Expert proficiency in developing and deploying multi-agent AI systems and reasoning frameworks (e.g., ReAct, Chain-of-Thought) for complex knowledge exploration, robust problem-solving, and decision support within search and retrieval contexts.
- Collaborate with cross-functional teams (AI Research, Data Engineering, Software Development).
Skills
- Minimum of 7 years of professional experience working as a Data Scientist in an industry setting
- Oversee the full lifecycle of large-scale AI projects.
- Understanding of coding AI (such as Claude Code) and experience in using it to scale up AI team deliveries
- Ensure timely project delivery and strategic goal alignment.
- Define robust software architecture for large-scale AI systems and project roadmaps.
- Translate high-level product requirements into actionable technical plans.
- Drive the implementation of scalable AI/ML platforms.
- Champion innovation and best practices across the organization.
- Foster a high-performing culture of technical excellence and continuous growth.
- Help to the leadership to align AI strategy effectively with client needs.
- A strong publication record in the top conferences in one of the AI, ML NLP, and decision science areas
- Experience in LLM post-training or fine-tuning.
Company info
- Company Description
- Air is the leader in Enterprise Readiness.
- Our mission is to establish readiness as a real-time condition that is continuously achieved.
- Our AI-native platform, Air Enterprise Readiness, aligns development, production, delivery, and sustainment into one coordinated execution system for government agencies and industrial suppliers.
Visa & Work Authorization
- Citizenship is required
This listing is sourced directly from Air's careers page and normalized into a canonical job model.