Sr. Artificial Intelligence Engineer (5361) (TS/SCI) (Ft. Belvoir, VA - Nolan Bldg)

About the role

SMX is seeking a Sr. Artificial Intelligence Engineer. This is a full-time onsite position in Ft. Belvoir, VA. Essential Duties & Responsibilities AI Model Lifecycle & MLOps Design, develop, and deploy machine learning models to achieve organizational mission objectives Implement MLOps processes and CI/CD pipelines in containerized or reproducible computing environments to support the full ML lifecycle Assess and address limitations of methods to deliver machine learning models in production Conduct AI risk assessments to ensure models and solutions are performing as designed Monitor, evaluate, and optimize ML model performance using appropriate metrics LLM Integration & Application Development Integrate AI solutions with cloud and enterprise IT infrastructure Design and implement AI-enabled applications leveraging Large Language Models (LLMs) and foundation models Automate development, testing, security, and deployment of AI/ML-enabled software Develop APIs and interfaces to enable secure, scalable interaction with AI models Implement Responsible AI best practices aligned with DoD AI Ethical Principles Technical Leadership & Collaboration Mentor and provide technical guidance to junior AI/ML engineers and data scientists. Serve as the technical lead for AI solution architecture, making final determinations on model selection and deployment frameworks. Analyze ML model outputs and translate results for technical and non-technical stakeholders Explain AI concepts and terminology clearly to cross-functional teams Identify low-probability, high-impact risks in ML training data and throughout the AI solution lifespan Research and evaluate the latest ML and AI tools, techniques, and best practices Write and document reproducible, secure code with proper error handling Mission Support Collaborate with stakeholders to address data privacy, PII, PHI, and data reusability concerns Ensure AI design and development activities are properly documented and updated Conduct hypothesis testing using statistical processes Use knowledge of business processes to create or recommend AI solutions Required Skills, Experience & Education Security Active TS security clearance and eligible for SCI and NATO read-on prior to starting work Meet all requirements to receive a privileged user account on a TS/SCI information system (e.g. Army Cloud Computing Service Provider) prior to starting work. The requirements are currently defined in DoDD 8140.01. Security+ or related DoDD 8140-relevant certification (or ability to obtain within 6 months of hire) Education and Experience Master's degree in Computer Science, Data Science, Software Engineering, Mathematics or Statistics, Computer Engineering, Information Technology or related field and 3+ years of experience in AI/ML engineering, with demonstrable expertise in model deployment and operationalization, or Bachelor's degree in Computer Science, Data Science, Software Engineering, Mathematics or Statistics, Computer Engineering, Information Technology or related field and 5+ years of experience in AI/ML engineering, with demonstrable expertise in model deployment and operationalization Hands-on experience with MLOps processes, CI/CD for ML, and containerized deployment environments (Docker, Kubernetes) Knowledge of Responsible AI frameworks and bias mitigation techniques Technical Skills Strong proficiency in machine learning theory, model development, and deployment Experience integrating AI solutions with LLMs (e.g., OpenAI GPT, Azure OpenAI, AWS Bedrock, or open-source alternatives) Proficiency in Python scripting and ML frameworks (TensorFlow, PyTorch, scikit-learn, Hugging Face) Knowledge of cloud platforms (AWS, Azure, GCP) and AI/ML service models (SaaS, IaaS, PaaS) Understanding of AI security risks, threats, and vulnerabilities, and mitigation strategies Familiarity with testing, evaluation, validation, and verification (T&E V&V) for AI systems Analytical & Communication Skills Ability to evaluate ML model effectiveness using appropriate metrics Skill in identifying and mitigating risks across the AI lifecycle Strong technical writing and presentation skills Ability to tailor technical information to diverse audiences Professional Attributes: Judgment - Assessing trade-offs and making informed technical decisions Problem-solving - Framing complex challenges and developing actionable solutions Execution orientation - Delivering results in dynamic, fast-paced environments Innovation & creativity - Recommending improvements and exploring emerging AI capabilities Risk-centered mindset - Understanding threats, vulnerabilities, and mission impacts Trustworthiness - Operating with integrity in highly sensitive environments Desired Skills/Experience Experience with DoD AI Ethical Principles (responsible, equitable, traceable, reliable, governable) Familiarity with NIST Risk Management Framework (RMF) or cybersecurity compliance s

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