Hiring: Senior AI Engineer Company: Thales Defense & Security, Inc. Location: Clarksburg, MD Job Posted Time: 2026-09-10 12:23:12 Employment Type: Hybrid Target Skills & Keywords : AWS, Airflow, Azure, CI/CD, Computer Vision, Deep Learning, Docker, FedRAMP, Git, Helm, Hugging Face, IaC, Jira, Kubeflow, Kubernetes, LLM, MLOps, MLflow, NLP, ONNX, PyTorch, Python, RAG, SageMaker, TensorFlow, TensorRT About the job Required Skills: •Lead the architecture, development, training, and deployment of AI/ML models, including traditional ML, deep learning, computer vision, NLP, and generative AI. •Design and manage end‑to‑end MLOps pipelines for data prep, training, model versioning, deployment, monitoring, and continuous retraining. •Define and enforce MLOps standards, governance, and responsible AI best practices across the enterprise. •Integrate AI solutions into on‑prem, cloud (Azure/AWS), and hybrid environments with strong focus on security and scalability. •Implement secure and responsible AI controls such as model hardening, privacy protections, explainability, and bias/fairness testing aligned with DoD/NIST frameworks. •Optimize model and inference performance for GPUs, on‑prem clusters, and edge environments. •Partner cross-functionally with security, cloud, DevOps, and application teams to productionize AI systems and resolve complex technical issues. •Ensure compliant handling of sensitive/classified data according to CMMC, NIST, DoD, and FedRAMP requirements. Qualifications: •The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. •U.S. Citizenship required. - Applicants selected may be subject to a government security investigation and must meet eligibility requirements for access to classified information. •Strong Python skills and experience with major ML frameworks (PyTorch/TensorFlow, scikit‑learn, Hugging Face). •Hands‑on experience building and maintaining MLOps pipelines (MLflow, DVC, Kubeflow, Airflow, Azure ML, SageMaker). •Proficiency deploying AI models using Docker, Kubernetes, and Helm, including GPU workloads. •Knowledge of AI security, adversarial ML, explainability, and responsible AI principles. •Proficiency with Git, CI/CD, IaC, and collaborative development practices. •Strong analytical, troubleshooting, and organizational skills. •Demonstrated capacity to lead, mentor, and work independently across cross‑functional teams. •Strong written and verbal communication skills for technical and non‑technical audiences. Compensation: •Medical insurance for self and eligible family members Interested candidates, please apply directly through the job posting on company's career page or try via AI auto apply on this platform. Don't miss this opportunity to join a forward-thinking team!