Lead AI/ML Engineer

This is a fully remote position, open to applicants in Colorado.

📋 Description

• Architect and integrate hybrid AI systems that blend traditional machine learning, deep learning, large language models (LLMs), and retrieval-augmented generation (RAG) pipelines.

• Design and implement scalable AI architectures, including APIs, microservices, and model-serving frameworks that seamlessly integrate with analytical, simulation, or operational systems.

• Oversee the complete AI/ML lifecycle—from data ingestion and feature engineering to training, deployment, and sustainment within secure DoD environments (IL5/IL6, ATO, GovCloud).

• Develop event-driven data pipelines and feature stores for both structured and unstructured data, encompassing text, imagery, and simulation outputs.

• Ensure Responsible AI practices by incorporating traceability, explainability, and confidence scoring into deployed systems.

• Establish and maintain MLOps pipelines (MLflow, Kubeflow, Airflow, Docker/Kubernetes) to facilitate continuous integration, retraining, and drift detection.

• Transition R&D prototypes into production, optimizing for mission constraints such as limited compute, edge environments, or disconnected operations.

• Provide technical leadership and mentorship, establishing standards for model quality, architectural design, and ethical AI deployment across various programs.

• Collaborate across engineering, data, and modeling teams to unify FTI’s AI portfolio, ensuring interoperability and reuse among mission systems.

• Assist in proposal and solution development by offering technical insights for AI/ML architectures, data strategies, and Responsible AI assurance frameworks.

⛳️ Requirements

• Active Secret clearance is required; TS/SCI is strongly preferred.

• Bachelor’s degree in Computer Science, Engineering, or a related technical field (Master’s or Ph.D. preferred).

• 10+ years of overall experience in AI/ML development, with at least 5 years in designing and deploying scalable AI/ML architectures, including a minimum of two full lifecycle implementations (from prototype to operational system).

• Proficiency in Python, PyTorch, TensorFlow, and contemporary ML frameworks.

• Experience in designing or deploying systems utilizing vector databases (Milvus, Pinecone, Weaviate), knowledge graphs, and semantic search frameworks.

• Proven capability to design event-driven data pipelines using Databricks, Spark, Flink, or Kafka.

• Demonstrated experience in deploying AI/ML systems within secure, classified, or edge environments.

• Familiarity with Responsible AI and assurance principles, including bias detection, explainability, human-machine collaboration, and hallucination prevention.

• Experience in integrating AI models into simulation, modeling, or operational planning systems is highly desirable.

• Strong communication and mentoring abilities, with the capacity to lead technically while remaining deeply engaged in hands-on work.

🏝️ Benefits

• Telecommute

• Health benefits