FTI - Frontier Technology Inc.

Distinguished AI/ML Engineering Lead

FTI - Frontier Technology Inc.

full-time

Posted on:

Location Type: Remote

Location: Remote • Alabama, Colorado, Florida, Ohio, Texas, Virginia • 🇺🇸 United States

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Job Level

Senior

Tech Stack

AirflowDockerKafkaKubernetesMicroservicesPythonPyTorchSparkTensorflowTypeScript

About the role

  • Architect and integrate hybrid AI systems that combine traditional machine learning, deep learning, large language models (LLMs), and retrieval-augmented generation (RAG) pipelines.
  • Design and deploy scalable AI architectures including APIs, microservices, and model-serving frameworks that integrate seamlessly with analytic, simulation, or operational systems.
  • Lead the full AI/ML lifecycle — from data ingestion and feature engineering through training, deployment, and sustainment within secure DoD environments (IL5/IL6, ATO, GovCloud).
  • Engineer event-driven data pipelines and feature stores for both structured and unstructured data, including text, imagery, and simulation outputs.
  • Ensure Responsible AI practices by embedding traceability, explainability, and confidence scoring into deployed systems.
  • Implement and maintain MLOps pipelines (MLflow, Kubeflow, Airflow, Docker/Kubernetes) to support 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.
  • Collaborate across engineering, data, and modeling teams to unify FTI’s AI portfolio, ensuring interoperability and reuse across mission systems.

Requirements

  • 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 5+ years designing and deploying scalable AI/ML architectures, including at least two full lifecycle implementations (from prototype to operational system).
  • Proficiency in Python, PyTorch, TensorFlow, and modern ML frameworks.
  • Experience designing or deploying systems using vector databases (Milvus, Pinecone, Weaviate), knowledge graphs, and semantic search frameworks.
  • Proven ability to design event-driven data pipelines using Databricks, Spark, Flink, or Kafka.
  • Demonstrated experience deploying AI/ML systems in secure, classified, or edge environments.
  • Familiarity with Responsible AI and assurance principles, including bias detection, explainability, human-machine teaming, and hallucination prevention.
  • Active Secret clearance required; TS/SCI strongly preferred.
  • Strong communication and mentoring skills, with the ability to lead technically while remaining deeply hands-on.
Benefits
  • Telecommute
  • Technical leadership and mentorship

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard skills
machine learningdeep learninglarge language modelsretrieval-augmented generationdata ingestionfeature engineeringMLOpsevent-driven data pipelinesPythonAI/ML architecture
Soft skills
communicationmentoringleadershipcollaboration
Certifications
Bachelor’s degreeMaster’s degreePh.D.Active Secret clearanceTS/SCI clearance