Senior AI Engineer

Thales Communications, Inc; Clarksburg (MA); Hybrid; USD 111,000 - 142,000; Full time

Benefits offered by this job

Competitive Salary

Yearly Incentive Plan

Medical insurance for self and family

401(k) with up to 7% company match

Tuition Reimbursement

Paid wellness, vacation, holidays

Parental leave

9/80 Schedule

Hybrid work environment

Job summary

Thales Defense & Security, Inc. seeks a Senior AI Engineer to lead AI/ML model development and MLOps, ensuring secure, compliant deployment across on-prem, cloud (Azure/AWS), and hybrid environments.

You will architect end-to-end MLOps pipelines, enforce governance per DoD/NIST, optimize GPU workloads, and mentor cross-functional teams in a security-conscious setting. Hybrid work from Clarksburg, MD campus.

Qualifications

• US Citizenship is required.
• Bachelor's degree in CS/AI/Engineering or related field; advanced degree a plus.
• 8+ years in software engineering/DevOps with 4+ years in AI/ML and MLOps.
• Strong Python and ML framework skills.
• Experience building MLOps pipelines (MLflow, DVC, Kubeflow, Airflow, Azure ML, SageMaker).
• Proficiency deploying AI models with Docker, Kubernetes, Helm; GPU workloads.

Responsibilities

• Lead AI/ML model architecture, training, and deployment.
• Design end-to-end MLOps pipelines for data prep, training, versioning, and retraining.
• Enforce responsible AI, DoD/NIST/CMMC-aligned governance and security.
• Integrate AI into on-prem/cloud/hybrid environments with secure practices.
• Develop tooling and CI/CD to automate AI workflows and monitoring.
• Mentor teams and document systems; drive issue resolution.

Skills

Python

MLOps

Docker

Kubernetes

CI/CD

Git

Security

AI/ML frameworks

Azure

AWS

GPU deployment

Edge deployment

Team leadership

Communication

Education

Bachelor's degree in CS/AI/Engineering

Advanced degree a plus

Tools

PyTorch

TensorFlow

scikit-learn

Hugging Face

MLflow

DVC

Kubeflow

Airflow

Azure ML

SageMaker

Docker

Kubernetes

Helm

Git

Jira Service Management

Job description

Thales Defense & Security, Inc. (TDSI) Headquartered in Clarksburg, MD, is a U.S. company that has been serving domestic and international defense Air, Land and Sea domains for 60+ years. With over 1,000 employees, TDSI and its four subsidiaries (Advanced Acoustic Concepts, Digital Receiver Technology, Tampa Microwave, and Trusted Cyber Technologies), supports U.S. Joint Services, special operations forces and multi-national partners with a variety of communication, visualization, signal intelligence/electronic warfare, and sensor/sonar capabilities. TDSI's key technologies include tactical handheld radios, expeditionary satellite terminals, helmet-mounted displays, optics and target recognition capability, advanced radars, undersea sensing and missile systems. Lives depend on what we do!

Top Benefits (Subject to terms of applicable policies/plans)

• 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)
• Hybrid working environment

We are seeking a Senior AI Engineer located in our Clarksburg, MD Campus. The Senior AI Engineer will report to the IT DevOps Manager.

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.

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.
• **Education:**Bachelor's degree in Computer Science, Data Science, AI, Engineering, Mathematics, or related field (or equivalent professional experience). Advanced degree a plus.
• **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.

Preferred but not required

• 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.

The annualized pay range for this role is $111,476.70 to $142,442.45 USD along with a target incentive compensation plan (ICP) of 5% The pay range provided is a good faith estimate representative of the experience level for the role described above. TDSI considers several factors when extending an offer, including but not limited to, the role, function and associated responsibilities, a candidate's work experience, location, education/training, and key skills.

For specific questions about this job posting, candidates may contact talent acquisition at

Thales Defense & Security, Inc. is committed to non-discrimination as applicable under federal, state and local laws. We are an E-Verify Employer.

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