ML Ops Engineer - Clearance Required

Responsibilities:

• Develop and validate machine learning models using technologies like Scikit-Learn and TensorFlow, focusing on generative AI applications.
• Deploy models to web-based applications and operationalize AI systems with robust, scalable pipelines across multiple environments.
• Design advanced data manipulation workflows with tools like Pandas and PySpark to support model training and analysis.

Qualifications:

• Requires a Bachelor's degree in Computer Science or related field and 3+ years of experience in ML engineering and MLOps.
• Must have expertise in Python, containerization with Docker/Kubernetes, and experience with Agile/Scrum methodologies and CI/CD practices.
• An active Secret Clearance is mandatory, with preferred qualifications including a Master's degree and experience with MLOps workflows like MLFlow.

Travel and Engagement:

• The role involves 10% travel and hybrid on-site engagement to build relationships with government customers and stakeholders.
• The engineer will mentor junior team members and contribute to technical narratives for proposals and strategic documentation within Army domains.