Senior AI Engineer

Thales Defense & Security, Inc. • CLARKSBURG, MD

35d • $111,477 - $142,442 • Hybrid

About The Position

Thales Defense & Security, Inc. (TDSI) is seeking a Senior AI Engineer to be located at their Clarksburg, MD Campus. The Senior AI Engineer will report to the IT DevOps Manager. This role involves leading the architecture, development, training, and deployment of AI/ML models, including traditional ML, deep learning, computer vision, NLP, and generative AI. The engineer will design and manage end-to-end MLOps pipelines, define and enforce MLOps standards, and integrate AI solutions into various environments with a focus on security and scalability. Responsibilities also include implementing secure and responsible AI controls, optimizing model performance, collaborating with other teams to productionize AI systems, ensuring compliant handling of sensitive data, building automation tooling, and mentoring engineering teams.

Requirements

• U.S. Citizenship required.
• Bachelor’s degree in Computer Science, Data Science, AI, Engineering, Mathematics, or related field (or equivalent professional experience).
• Minimum 8 years of progressive experience in software engineering, DevOps, platform engineering, data engineering, or infrastructure, including at least 4 years hands-on AI/ML engineering and MLOps (designing, deploying, monitoring, and operating production AI/ML systems).
• Strong transferable experience from software, DevOps, SRE, or data platform roles is highly valued given the relative newness of pure AI careers.
• 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.
• Experience working with secure data handling and controlled environments.
• Proficiency with Git, CI/CD, IaC, and collaborative development practices.
• Experience with ticketing/ITSM tools (e.g., Jira Service Management).
• Strong analytical, troubleshooting, and organizational skills.
• Ability to lead, mentor, and work independently across cross‑functional teams.
• Strong written and verbal communication skills for technical and non‑technical audiences.

Nice To Haves

• Advanced degree in CS, AI, ML, or related fields.
• Experience with generative AI, LLMs, RAG, vector databases, and LLMOps.
• Experience with on‑prem GPU clusters, HPC environments, or schedulers (Slurm, Run:ai).
• Model optimization and edge deployment experience (quantization, pruning, TensorRT, ONNX).
• Experience in defense or other highly regulated environments with DoD/NIST/CMMC frameworks.

Responsibilities

• 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.
• Collaborate 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.
• Build Python tooling, reusable components, and CI/CD integrations to support automation and platform maturity.
• Lead proofs‑of‑concept, maintain documentation, guide monitoring and incident response, and mentor engineering teams.

Benefits

• Competitive Salary
• Yearly Incentive Compensation Plan
• Medical insurance for self and eligible family members
• Generous 401(k) program- up to 7% company contribution and 100% immediate vesting
• Tuition Reimbursement
• Paid wellness, vacation, and holiday leave
• Paid maternity, paternity, and parental leave
• 9/80 Work Schedule (every other Friday off)

What This Job Offers

• Job Type: Full-time
• Career Level: Senior