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HomeCompaniesCareers Ftidefense Icims ComDistinguished AI/ML Engineering Lead

Distinguished AI/ML Engineering Lead

Careers Ftidefense Icims Com · Washington, D.C., UNAVAILABLE, US · Remote · Active · $140,000–$220,000 / year · iCIMS

Job facts

FieldValue
CompanyCareers Ftidefense Icims Com
TitleDistinguished AI/ML Engineering Lead
Normalized title-
Department / teamEngineering
LocationWashington, D.C., UNAVAILABLE, United States
Work modelRemote / Remote
Employment typeFull Time
Salary$140,000–$220,000 / year
Statusactive
ATS provideriCIMS
Posted / first seen2024-06-06 / 2026-05-31
Changed / last seen2026-06-06 / 2026-06-06

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Company jobsActive postings from Careers Ftidefense Icims Com.Open
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City jobsActive postings in Washington, D.C..Open
Department jobsActive postings in Engineering.Open
Work model jobsActive Remote postings.Open
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Original postingCanonical source or apply URL captured from the ATS.Open

Linked records

CompanyCareers Ftidefense Icims Com
Sourced287a8af-66df-4e8f-8390-998e0eae44f0
ATS provideriCIMS

Description

Overview Frontier Technology Inc. (FTI) delivers mission-focused solutions to the Department of Defense and Intelligence Community through advanced engineering, digital transformation, and program execution expertise. We help our customers solve complex challenges and achieve mission success by integrating people, process, and technology. FTI is seeking a Distinguished AI/ML Engineer to serve as a technical leader, architect, and integrator — designing, building, deploying, and sustaining AI systems that transform complex mission data into trusted, explainable insights. This is a hands-on builder role, not an analytics management position. The ideal candidate is equally comfortable writing model code, standing up ML pipelines, and integrating AI inference services into operational systems within secure environments. The right candidate blends deep AI/ML engineering expertise with system-level architecture leadership and an ability to unify data engineering, simulation modeling, and responsible AI principles into scalable, mission-ready capabilities. Responsibilities 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. Provide technical leadership and mentorship, setting standards for model quality, architectural design, and ethical AI deployment across programs. Collaborate across engineering, data, and modeling teams to unify FTI’s AI portfolio, ensuring interoperability and reuse across mission systems. Support proposal and solution development, providing technical inputs for AI/ML architectures, data strategies, and Responsible AI assurance frameworks. Education/Qualifications 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. Experience integrating AI models into simulation, modeling, or operational planning systems is highly desirable. Experience transitioning R&D systems into accredited production environments. Active Secret clearance required; TS/SCI strongly preferred. Strong communication and mentoring skills, with the ability to lead technically while remaining deeply hands-on. For this role, the compensation range is $140k-$220k. *Note: Starting pay will be based on a number of factors and commensurate with the candidate’s residence location, qualifications & experience. #LI-KM1 #LI-Remote

Full job record

Job ID1aa24720161321182748104dde54a8a65d42659a
Org IDfbe06776-75b5-4c67-b256-8469b443a85e
Source IDd287a8af-66df-4e8f-8390-998e0eae44f0
Board IDd287a8af-66df-4e8f-8390-998e0eae44f0
Providericims
Provider Job Key6877
TitleDistinguished AI/ML Engineering Lead
Normalized Title
Statusactive
Activeyes
Location TextWashington, D.C., UNAVAILABLE, US
DepartmentEngineering
Team
Employment Typefull_time
Workplace Typeremote
Remote Policyremote
CountryUnited States
RegionUNAVAILABLE
CityWashington, D.C.
Salary RawOverview Frontier Technology Inc. (FTI) delivers mission-focused solutions to the Department of Defense and Intelligence Community through advanced engineering, digital transformation, and program execution expertise. We help our customers solve complex challenges and achieve mission success by integrating people, process, and technology. FTI is seeking a Distinguished AI/ML Engineer to serve as a technical leader, architect, and integrator — designing, building, deploying, and sustaining AI systems that transform complex mission data into trusted, explainable insights. This is a hands-on builder role, not an analytics management position. The ideal candidate is equally comfortable writing model code, standing up ML pipelines, and integrating AI inference services into operational systems within secure environments. The right candidate blends deep AI/ML engineering expertise with system-level architecture leadership and an ability to unify data engineering, simulation modeling, and responsible AI principles into scalable, mission-ready capabilities. Responsibilities 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. Provide technical leadership and mentorship, setting standards for model quality, architectural design, and ethical AI deployment across programs. Collaborate across engineering, data, and modeling teams to unify FTI’s AI portfolio, ensuring interoperability and reuse across mission systems. Support proposal and solution development, providing technical inputs for AI/ML architectures, data strategies, and Responsible AI assurance frameworks. Education/Qualifications 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. Experience integrating AI models into simulation, modeling, or operational planning systems is highly desirable. Experience transitioning R&D systems into accredited production environments. Active Secret clearance required; TS/SCI strongly preferred. Strong communication and mentoring skills, with the ability to lead technically while remaining deeply hands-on. For this role, the compensation range is $140k-$220k. *Note: Starting pay will be based on a number of factors and commensurate with the candidate’s residence location, qualifications & experience. #LI-KM1 #LI-Remote
Salary Min140,000
Salary Max220,000
Salary CurrencyUSD
Salary Periodyear
Source URLhttps://careers-ftidefense.icims.com/jobs/6877/distinguished-ai-ml-engineering-lead/job
Apply URLhttps://careers-ftidefense.icims.com/jobs/6877/distinguished-ai-ml-engineering-lead/job
First Seen At2026-05-31 18:46:59Z
Last Seen At2026-06-06 08:37:41Z
Last Checked At2026-06-06 08:37:41Z
Last Changed At2026-06-06 08:37:41Z
Inactive At
Source Posted At2024-06-06 08:37:41Z
Source Updated At2026-05-29 15:47:06Z
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