AI/ML Engineer, Mid (Clearance Required)

Job Responsibilities

• Design, develop, and containerize machine learning (ML) models using modern frameworks and tools, including PyTorch, Ray, Docker, and FastAPI.
• Deploy, manage, and scale production ML workloads on Kubernetes.
• Integrate AI/ML capabilities into full-stack applications using Python-based backend services and JavaScript frontend technologies.
• Ensure model reliability, performance, and maintainability throughout the deployment lifecycle.
• Architect cloud-native ML infrastructure on AWS.
• Develop and maintain DevOps and MLOps pipelines to streamline model development, testing, deployment, and monitoring.
• Deploy and support AI/ML systems within secure, classified, and high side environments.
• Evaluate and adopt state-of-the-art AI/ML models, frameworks, and emerging technologies.
• Architect scalable and resilient infrastructure to support evolving AI/ML workloads and mission requirements.
• Establish and promote best practices for production-grade machine learning (ML) systems, including security, observability, and governance.
• Provide technical guidance and thought leadership across AI/ML initiatives and engineering teams.

Required Qualifications

• Active Top Secret/SCI (TS/SCI) clearance with a current Polygraph.
• Bachelor’s degree with 5 years of related experience; OR Master's degree with 3 years of related experience; OR associate’s degree with 8 years of related experience; OR High School diploma/GED with 11 years of related experience.
• Experience deploying machine learning (ML) models to production, including large language models (LLMs).
• Strong proficiency with machine learning (ML) frameworks and containerization technologies (e.g., PyTorch, Docker, and Kubernetes).
• Full-stack software development experience using Python and JavaScript.
• Demonstrated experience implementing MLOps and DevOps best practices, including CI/CD, model deployment, monitoring, and automation.
• Working knowledge of AWS cloud services and infrastructure.
• U.S. Citizenship is required.

Desired Qualifications

• Expert-level proficiency in Python with extensive experience across leading machine learning (ML) frameworks, including TensorFlow, PyTorch, and scikit-learn.
• Proven ability to design and implement end-to-end machine learning (ML) pipelines, spanning data ingestion, feature engineering, model training, evaluation, deployment, and monitoring.
• Extensive experience with large language models (LLMs), including fine-tuning, prompt engineering, retrieval-augmented generation (RAG), agentic workflows, and responsible AI practices.
• Expertise in advanced machine learning (ML) techniques, including deep learning, reinforcement learning, generative models, ensemble methods, and modern model optimization approaches.
• Demonstrated experience leading technical architecture decisions and mentoring engineers on machine learning (ML) best practices, software engineering standards, experimentation, code quality, and research methodology.
• Proficiency with containerization and orchestration technologies, including Docker and Kubernetes, to support scalable model serving, A/B testing, and canary releases/deployments.
• Hands-on experience architecting and deploying scalable machine learning (ML) solutions on cloud platforms (e.g., AWS SageMaker, Azure Machine Learning, Google Vertex AI) with a focus on scalability, reliability, and cost optimization.
• Proven track record of designing and implementing production-grade MLOps infrastructure, including automated model retraining, monitoring, drift detection, and CI/CD pipelines using tools such as MLflow, Kubeflow, and SageMaker.
• Strong background in distributed computing and big data technologies such as Apache Spark, Ray, and Dask for efficient model training and inference.
• Experience contributing to or publishing applied ML research, patents, conference presentations, or open-source projects.
• 7+ years of experience designing, developing, and deploying machine learning systems at scale in production environments.