AI/Machine Learning Engineer

Role Overview We are seeking an AI / Machine Learning Engineer to design, develop, and deploy scalable machine learning solutions that solve real-world national security challenges. This role will work closely with engineering, product, and operations teams. The ideal candidate combines extremely strong technical expertise with practical problem-solving skills and proven skill at designing and developing AI technologies. The primary focus is on autonomous systems, subsystems and systems integration. Key Responsibilities Model Development & Deployment Design and develop AI capable of performing in uncertain and dynamic or unstructured real-world scenarios Design, build, train, and optimize machine learning models (supervised, unsupervised, and/or deep learning) Develop end-to-end ML pipelines, from data ingestion and feature engineering to model evaluation and deployment Deploy models into production environments and monitor performance, drift, and reliability Data & Engineering Collaboration Work with structured and unstructured data from multiple sources Collaborate with software engineers to integrate ML models into applications, APIs, or platforms Partner with stakeholders to translate business needs into ML-driven solutions Evaluation & Optimization Evaluate model performance using appropriate metrics Tune models for accuracy, efficiency, scalability, and interpretability Implement versioning, testing, and documentation for ML assets Governance & Best Practices Follow secure coding practices and data privacy standards Document models, assumptions, and limitations clearly Contribute to ML best practices, standards, and reusable components Required Qualifications Bachelor’s degree in Computer Science, Data Science, Engineering, Mathematics, or a related field (or equivalent experience) Strong proficiency in Python and common ML libraries (e.g., TensorFlow, PyTorch, scikit-learn) Experience working with data pipelines, APIs, and cloud-based environments Understanding of core ML concepts, including model training, validation, and deployment Experience with SQL and data manipulation tools Experience with containerization (Docker, Kubernetes) Familiarity with data visualization tools Preferred Qualifications Doctorate or Master’s degree in a relevant field Experience deploying ML models in production environments Familiarity with MLOps tools and practices (CI/CD, monitoring, model lifecycle management) Experience with cloud platforms and modern compute Knowledge of NLP, computer vision, or large language models (LLMs) Experience with agent, agentic and cognitive AI Prior experience supporting government, defense, or enterprise customers Experience working in regulated or compliance-driven environments