Machine Learning/AI Engineer

Element Solutions is a partner at the intersection of innovation and client needs, focusing on creating digital solutions. They are seeking a highly skilled Machine Learning / AI Engineer to design, develop, and deploy production-grade AI and machine learning solutions for a federal government program.

Responsibilities:

• 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
• Experience deploying models in cloud environments (AWS, Azure, or GCP)
• Familiarity with MLOps tools and frameworks (e.g., MLflow, Kubeflow, SageMaker, Vertex AI)
• Experience with streaming or real-time inference systems
• Background in predictive maintenance, anomaly detection, or operational analytics use cases
• Familiarity with Docker, Kubernetes, and CI/CD pipelines for machine learning systems
• Experience supporting healthcare (e.g., CMS), or other federal mission systems