Machine Learning/AI Engineer

Element

Machine Learning/AI Engineer developing scalable AI solutions for federal government programs. Handling model lifecycle from design to deployment in regulated environments.

Posted 5/2/2026full-timeRemote • 🇺🇸 United StatesMid-LevelSenior💰 $135,000 - $145,000 per yearWebsite

Tech Stack

Tools & technologies

CloudPythonPyTorchScikit-LearnSQLTensorflow

About the role

Key responsibilities & impact

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

What you’ll need

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.

Benefits

Comp & perks

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

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

machine learningAI engineeringPythonPyTorchTensorFlowSQLLarge Language Modelsmodel evaluationfeature engineeringdata preprocessing

Soft Skills

analytical skillsproblem-solving skillscommunication skillscollaboration skillsattention to detailindependenceadaptabilitystakeholder engagementtechnical documentationAgile methodology