Machine Learning/AI Engineer

Role Overview

• Develop and deploy at least three (3) production-grade AI/ML models, including use cases such as predictive maintenance, anomaly detection, classification, forecasting, or optimization.
• Design, build, and maintain end-to-end machine learning pipelines, including data preprocessing, feature engineering, model training, evaluation, and deployment.
• Apply deep expertise in PyTorch and/or TensorFlow to develop and fine-tune advanced machine learning and deep learning models.
• Implement and support scalable model serving architectures, ensuring high availability, low latency, and secure inference in production environments.
• Collaborate with data engineers to access, transform, and prepare large-scale datasets for model training and inference.
• Partner with product owners, analysts, and stakeholders to translate business requirements into machine learning solutions.
• Monitor model performance in production, including drift detection, accuracy tracking, and retraining strategies.
• Ensure compliance with federal security, privacy, and governance standards in all AI/ML implementations.
• Participate in Agile development cycles, including sprint planning, design reviews, and technical demonstrations.
• Document model architectures, training methodologies, and deployment processes for maintainability and auditability.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, Engineering, Mathematics, or related field (or equivalent experience).
• 3+ years of experience in machine learning, data science, or AI engineering roles.
• Proven experience delivering production-grade machine learning models in real-world environments.
• Expert proficiency in Python and ML frameworks (scikit-learn, TensorFlow, PyTorch).
• Advanced SQL development experience, including complex queries, performance tuning, and data transformation logic.
• Experience leveraging Large Language Models (LLMs) in development.
• Understanding of core concepts such as context windows, prompt design, and input/output structures, with the ability to apply AI tools effectively in building and enhancing solutions.
• Experience building and deploying models using scalable serving frameworks (e.g., REST APIs, containerized deployments, or cloud-based inference services).
• Experience working with large-scale structured and unstructured datasets.
• Strong understanding of machine learning concepts including supervised/unsupervised learning, deep learning, model evaluation, and feature engineering.
• Experience working in the federal government or other highly regulated environments with security and compliance requirements.
• Strong analytical and problem-solving skills.
• Ability to communicate complex technical concepts to non-technical stakeholders.
• Strong collaboration skills across engineering, data, and product teams.
• Ability to work independently in a fast-paced, mission-driven environment.
• High attention to detail with a focus on model reliability and production readiness.
• US Citizenship or Permanent Residency required.
• Must reside in the Continental US.
• Depending on the government agency, specific requirements may include public trust background check or security clearance.

Tech Stack

• Cloud
• Python
• PyTorch
• Scikit-Learn
• SQL
• Tensorflow

Benefits

• health care
• dental
• vision
• life insurance
• 401(k)
• paid time off including PTO, holidays, and any other paid leave required by law