AI / ML Engineer - WISRD Platform Development

Location

Hybrid (Maryland preferred) Remote options available for highly qualified candidates.

Employment Type

Full-Time

Clearance Requirement

Must be a U.S. Citizen and eligible to obtain a DoD Secret clearance.

Company Overview

CyOne is a mission-driven software company dedicated to delivering cutting-edge capabilities to the U.S. Department of War and allied partners. Our flagship platform, WISRD (Wide-area ISR Discovery), is key to enhancing multi-domain situational awareness, providing intelligence support for targeting, and orchestrating ISR operations across various environments including cloud and tactical edge.

WISRD is actively utilized in operational settings and aligns with emerging Next Generation Command and Control (NGC2) initiatives. Our platform effectively integrates and fuses data from diverse ISR sensors and mission systems to facilitate real-time decision-making in complex operational scenarios.

Position Overview

We are searching for an AI / ML Engineer to spearhead the development of an AI-enabled assistant within the WISRD platform. This feature will empower analysts and operators to interact with mission data, streamline workflows, generate insights, and initiate actions via natural language queries.

This is a vital, hands-on engineering role aimed at creating production-grade AI systems that function efficiently in enterprise and tactical edge contexts, particularly in disconnected, degraded, intermittent, and low-bandwidth (DDIL) conditions. The selected candidate will act as the technical lead for AI integration within WISRD, overseeing design, implementation, and deployment from the initial concept to operational use.

Key Responsibilities

• Design and build AI capabilities that enable users to query ISR data and trigger workflows through natural language queries.
• Develop and maintain Retrieval-Augmented Generation (RAG) pipelines focused on structured and unstructured operational data.
• Implement and refine vector search and embedding pipelines to deliver precise and reliable outputs.
• Establish a provider-agnostic LLM integration layer supporting various AI services.
• Create AI systems functional in DDIL environments.
• Lead model selection, fine-tuning, and evaluation leveraging domain-specific datasets.
• Develop backend services and APIs for orchestration, context management, and intent parsing of AI capabilities.
• Integrate AI solutions into the WISRD platform for seamless user interaction and workflow automation.
• Set up MLOps pipelines to monitor and improve model performance continuously.
• Ensure all AI solutions comply with security, data handling, and operational requirements across multiple enclaves.

Work Environment

• Collaborative engineering team focused on mission success.
• Direct engagement with developers, DevOps engineers, and subject matter experts.
• Agile development setting with quick iteration cycles.
• Opportunity involved in real-world operational deployments.

Compensation & Benefits

• Competitive salary based on experience.
• Comprehensive benefits package including medical, dental, and vision coverage.
• Paid time off and holidays.
• Opportunities for professional development and career advancement.

Required Qualifications

Technical Skills

• Proven experience designing and implementing RAG pipelines in production.
• Familiarity with vector databases (e.g., pgvector, Qdrant, Pinecone, Weaviate).
• Solid understanding of embeddings and semantic search.
• Experience fine-tuning LLMs using frameworks like Hugging Face.
• Proficient in Python and contemporary backend frameworks (e.g., FastAPI).
• Experience with PostgreSQL or similar relational databases.
• Knowledge of REST APIs and streaming technologies.

Infrastructure & Tools

• Experience using Docker and containerized deployments.
• Familiarity with Kubernetes and distributed systems.
• Experience with model serving frameworks.
• Experience with GPU-based compute environments.

Experience

• 3+ years of experience in AI/ML engineering or related fields.
• Demonstrated experience deploying AI/LLM-based systems into production environments.
• Background in handling structured or operational data.
• Able to work independently in a dynamic environment.

Preferred Qualifications

• Knowledge of hybrid search techniques (vector + keyword retrieval).
• Experience with model quantization methods.
• Experience with deploying AI systems to edge or constrained environments.
• Familiarity with enterprise platforms like Cloudera ML.
• Experience with ISR systems, geospatial data, or defense command environments.
• Experience in the DoD or intelligence community.
• Familiarity with front-end technologies like Angular or TypeScript.
• Active DoD security clearance is a plus.

Compensation details: $165,000 - $185,000 Yearly Salary

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