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Remote Machine Learning/AI Engineergrabjobs • United States
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Remote Machine Learning/AI Engineer

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    United States
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    United States
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Über

Who is Element?
We serve as a partner at the intersection of innovation and our clients' needs, efficiently crafting meaningful user experiences for government and commercial customers. By breaking down complex problems to their fundamental elements, we create modern digital solutions that drive efficiencies, maximize taxpayer dollars, and deliver essential outcomes that serve the people.
Why Work at Element?
Make an impact that resonates-join our vibrant team and discover how you can improve lives through digital transformation.
Our talented professionals bring unparalleled energy engagement, setting a higher standard for impactful work. Come be a part of our team and shape a better future.
Position Summary:
We are seeking a highly skilled and motivated Machine Learning / AI Engineer to support a federal government program focused on designing, developing, and deploying production-grade artificial intelligence and machine learning solutions. The role will focus on building scalable, secure, and high-performing AI models that support mission-critical decision-making and operational efficiency.
The Machine Learning/AI Engineer will work across the full model lifecycle—from data preparation and feature engineering to model training, deployment, and monitoring—in a regulated government environment.
Key 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.
Minimum 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.
Preferred Qualifications
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.
$135,000 - $145,000 a year
The likely salary range for this position is $135,000-$145,000.
The salary offered will depend on several factors including, but not limited to, relevant experience, skills, education, geographic location, internal equity, business needs, and other factors permitted by law. Posted pay ranges are a general guideline only and are not a guarantee of compensation or salary. Our People
We invest in the lives of our employees, both in and out of the workplace, by providing competitive pay and benefits packages. Benefits offered may include health care, dental, vision, life insurance; 401(k); paid time off including PTO, holidays, and any other paid leave required by law.
Location Be in your Element. We are a remote first company based out of Washington, DC.
Element is an equal opportunity employer
All qualified applicants will receive consideration for employment without regard to age, ancestry, race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status, marital status, protected veteran status, or any other legally protected class.
We believe in a world where solutions we build improve the lives of those who use them.
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