AI / ML Engineer
Role details
Job location
Tech stack
Job description
CyOne is seeking an AI / ML Engineer to lead the development of an AI-enabled assistant embedded within the WISRD platform. This capability will enable analysts and operators to query mission data, navigate workflows, generate insights, and trigger actions using natural language.
This is a high-impact, hands-on engineering role focused on building production AI systems that operate across enterprise and tactical edge environments, including disconnected, degraded, intermittent, and low-bandwidth (DDIL) conditions.
The selected candidate will serve as the technical lead for AI capabilities within WISRD, owning architecture, implementation, and delivery from concept through operational deployment., * Design and build AI capabilities that enable users to query ISR data, generate insights, and trigger mission workflows through natural language
- Develop and maintain Retrieval-Augmented Generation (RAG) pipelines grounded in structured and unstructured operational data
- Implement and optimize vector search, embedding pipelines, and hybrid retrieval strategies to ensure accurate, reliable outputs
- Build and maintain a provider-agnostic LLM integration layer supporting both enterprise AI services and self-hosted models
- Design AI systems that operate effectively in DDIL (disconnected, degraded, intermittent, low-bandwidth) environments
- Lead model selection, fine-tuning (LoRA/QLoRA), and evaluation using domain-specific datasets
- Develop AI backend services and APIs, including orchestration, context management, and intent parsing
- Integrate AI capabilities into the WISRD platform for real-time user interaction and workflow automation
- Establish MLOps pipelines, monitor model performance (accuracy, latency, cost), and continuously improve system quality
- Ensure AI solutions meet security, data handling, and multi-enclave operational requirements
Work Environment
- Small, collaborative engineering team
- Direct interaction with developers, DevOps engineers, and mission subject matter experts
- Agile development environment with rapid iteration cycles
- Opportunity to support real-world operational deployments
Requirements
Technical Skills
- Experience designing and implementing RAG pipelines in production
- Experience with vector databases (e.g., pgvector, Qdrant, Pinecone, Weaviate)
- Strong understanding of embeddings and semantic search
- Experience fine-tuning LLMs (LoRA / QLoRA) using Hugging Face or similar
- Proficiency in Python and modern backend frameworks (e.g., FastAPI)
- Experience with PostgreSQL or similar relational databases
- Experience with REST APIs and streaming technologies
Infrastructure & Tools
- Experience with Docker and containerized deployments
- Familiarity with Kubernetes and distributed systems
- Experience with model serving frameworks (e.g., vLLM, TGI, Ollama)
- Experience with GPU-based compute environments
Experience
- 3+ years of experience in AI/ML engineering or related field
- Experience deploying AI/LLM-based systems to production
- Experience working with structured or operational data
- Ability to work independently in a fast-paced environment, * Experience with hybrid search (vector + keyword retrieval)
- Experience with model quantization techniques (GGUF, GPTQ, AWQ)
- Experience deploying AI systems to edge or resource-constrained environments
- Familiarity with Cloudera ML or similar enterprise platforms
- Experience with ISR systems, geospatial data, or mission command environments
- Background in DoD, intelligence community, or other regulated environments
- Familiarity with Angular or TypeScript
- Active DoD security clearance
Benefits & conditions
Health insurance, Paid time off, Vision insurance, Dental insurance, Paid holidays, Opportunities for advancement, * Competitive salary based on experience
- Comprehensive benefits package (medical, dental, vision)
- Paid time off and holidays
- Opportunities for professional growth and advancement