Job Requirements Fort Belvoir, VA Secret Polygraph not specified Senior Level Career (10+ yrs experience) $140,000 - $160,000 Job Description Job Purpose GCubed Enterprises, LLC. is seeking an AI/ML Engineer to design, build, and deploy machine learning models and AI-powered solutions that solve real business problems. This role will work closely with engineering, product, data, and business teams to turn complex data into scalable, practical, and measurable solutions. The ideal candidate has strong technical skills, curiosity, problem-solving ability, and experience with Large Language Models (LLMs). Essential Functions of the Job

• Design, develop, train, and deploy machine learning and AI models.
• Build scalable ML pipelines for data processing, model training, testing, and deployment.
• Work with structured and unstructured data, including text, images, documents, and large datasets.
• Collaborate with data engineers, software engineers, and product teams to integrate AI/ML solutions into applications.
• Evaluate model performance and improve accuracy, efficiency, reliability, and scalability.
• Research and apply current AI/ML methods, tools, and best practices.
• Support development of predictive models, recommendation systems, NLP tools, automation workflows, and generative AI solutions.
• Monitor deployed models and troubleshoot issues related to drift, bias, performance, and data quality.
• Document model architecture, assumptions, limitations, and performance metrics.
• Ensure responsible AI practices, including privacy, security, fairness, and compliance. Required Qualifications
• Minimum active secret clearance
• Bachelor's degree in Computer Science, Data Science, Machine Learning, Statistics, Mathematics, Engineering, or related field.
• 3+ years of experience in machine learning, AI, data science, or software engineering.
• Strong programming experience with Python.
• Experience with ML libraries and frameworks such as TensorFlow, PyTorch, Scikit-learn, Keras, or XGBoost.
• Experience building and deploying machine learning models in production.
• Strong understanding of algorithms, model evaluation, feature engineering, and statistical analysis.
• Experience working with large datasets and data processing tools.
• Familiarity with APIs, cloud platforms, and modern software development practices.
• Ability to communicate technical concepts clearly to non-technical stakeholders.
• Security+ certification Preferred Qualifications
• Master's degree or PhD in a related field.
• Experience with Generative AI, LLMs, NLP, computer vision, or deep learning.
• Experience with tools such as LangChain, Hugging Face, OpenAI API, Azure AI, AWS SageMaker, or Google Vertex AI.
• Experience with MLOps tools such as MLflow, Kubeflow, Airflow, Docker, Kubernetes, or CI/CD pipelines.
• Experience with SQL, Spark, Databricks, Snowflake, or cloud data warehouses.
• Knowledge of model governance, AI ethics, bias testing, and data privacy standards.

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