AI/ML Engineer - WISRD Platform & Tactical Edge

- Demonstrated experience in designing and implementing Retrieval-Augmented Generation (RAG) pipelines in production environments - Proficient in utilizing vector databases (e.g., pgvector, Qdrant, Pinecone, Weaviate) - Strong knowledge of embeddings and semantic search methodologies - Experience in fine-tuning Large Language Models (LLMs) (LoRA / QLoRA) using Hugging Face or similar tools - Proficient in Python and contemporary backend frameworks (e.g., FastAPI) - Familiarity with PostgreSQL or analogous relational databases - Experience with REST APIs and streaming technologies - Familiarity with Docker for containerized deployments - Knowledge of Kubernetes and distributed systems - Proficient in model serving frameworks (e.g., vLLM, TGI, Ollama) - Experience in GPU-based compute environments - A minimum of 3 years in AI/ML engineering or a related sector - Experience in deploying AI/LLM-based systems in production - Background in working with structured or operational data - Capacity to work autonomously in a dynamic environment - Preferred: experience with hybrid search (vector + keyword retrieval) - Preferred: knowledge of model quantization techniques (GGUF, GPTQ, AWQ) - Preferred: exposure to deploying AI applications to edge or resource-limited environments - Preferred: familiarity with Cloudera ML or similar enterprise solutions - Preferred: experience in ISR systems, geospatial data, or mission command environments - Preferred: background in the Department of Defense, intelligence community, or regulated settings - Preferred: knowledge of Angular or TypeScript - Preferred: active Department of Defense security clearance