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Machine Learning/AI Engineer

1 month ago
United States
Full-time
Mid Level
AI Engineer
Software Development
Agile AWS Azure CI/CD Docker GCP Kubeflow Kubernetes LLM Machine Learning MLflow MLOps Python PyTorch REST API SageMaker Scikit-learn SQL TensorFlow Vertex AI
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Element Solutions

Element Solutions

Element Solutions is a human-centered agency specializing in government modernization and digital transformation, offering expertise in DevOps, FHIR, and data analytics.

Professional Services
11-50
Founded 2009
View All Jobs 10

Description

  • Develop and deploy at least three production-grade AI/ML models for use cases such as predictive maintenance, anomaly detection, classification, forecasting, or optimization.
  • Design, build, and maintain end-to-end machine learning pipelines covering data preprocessing, feature engineering, model training, evaluation, and deployment.
  • Apply PyTorch and/or TensorFlow to develop and fine-tune advanced machine learning and deep learning models.
  • Implement scalable model serving architectures that support high availability, low latency, and secure inference in production.
  • Collaborate with data engineers to access, transform, and prepare large-scale datasets for training and inference.
  • Partner with product owners, analysts, and stakeholders to translate business requirements into machine learning solutions.
  • Monitor production model performance, including drift detection, accuracy tracking, and retraining strategies.
  • Ensure compliance with federal security, privacy, and governance standards in AI/ML implementations.
  • Participate in Agile ceremonies such as 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 a 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 such as scikit-learn, TensorFlow, and PyTorch.
  • Advanced SQL development experience, including complex queries, performance tuning, and data transformation logic.
  • Experience leveraging Large Language Models (LLMs) in development, including understanding of context windows, prompt design, and input/output structures.
  • Experience building and deploying models using scalable serving frameworks such as 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 and unsupervised learning, deep learning, model evaluation, and feature engineering.
  • Experience working in the federal government or another highly regulated environment 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.
  • Public trust background check or security clearance may be required depending on the government agency.

Benefits

  • Competitive pay with a likely salary range of $135,000 to $145,000 per year.
  • Health care benefits, including dental and vision coverage.
  • Life insurance.
  • 401(k) retirement plan.
  • Paid time off, including PTO and holidays.
  • Other paid leave required by law.
  • Remote-first work environment.
  • Opportunity to work on impactful federal mission systems and digital transformation work.

Interested in this position?

Apply directly on the company website

Apply Now

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