Remote Sr. AI.ML Engineer (MLaaS / Federal )

A leader in technology within the federal space is seeking a proven Senior AI/ML Engineer to continue the growth of our AI/ML capability, support our client contract, and will work with and provide guidance on the organization's implementation of large datasets with specific goals on maintaining and enhancing the quality of data (more than 500M records). Efforts will include implementation and continuous improvement of Machine Learning as a Service (MLaaS), Graph Data Science, and other informed algorithms and AI/ML techniques to improve data usability.Responsibilities:• You'll analyze complex datasets to assess performance or find new patterns• You'll apply machine learning techniques to data sets related to immigration• You'll present results to a diverse audience in presentation or report form• You'll lead architectural design, technical support, and advisement services to ensure identity management system technologies are integrated and meeting the appropriate security requirements• You’ll support leadership who engage with senior level executives at a public facing Federal agency and provide subject matter expertise in security architecture and other key domain areasQualifications:• Must be US Citizen with the ability to obtain and maintain a Public Trust• Minimum of ten (10) years of IT experience, focusing on enterprise data architecture and management.• Experience applying graph data science solutions (e.g., leveraging tools like Python, Pandas, NumPy, Sidekick Learn, Neo4j)• Experience in modeling solutions in AWS that us AI/ML algorithms• Least ten (10) years of proven expertise in Relational and Dimensional Data Modeling.• Experience of cloud architecture, specifically AWS, as it relates to data processing (i.e., EC2, S3, Redshift, etc.).• Able to define & maintain BI/Data Warehouse methodologies, standards, and industry best practices.• Experience leading and architecting enterprise-wide initiatives, specifically system integration, data migration, transformation, data warehouse build, data mart build, data lakes implementation / support, as well as O&M etc. for a large enterprise.