MANTECH seeks a motivated, career and customer-oriented Lead Machine Learning Engineer to join our Data and AI Practice. This position requires full-time on-site presence in Chantilly, VA. In this role, you will collaborate with a team of architects, developers, data engineers, and data scientists to deliver advanced AI-driven data exploitation tools to meet the evolving sensemaking needs of national security and law enforcement missions. The ideal candidate will have deep machine learnings skills and experience, a firm understanding of ML Ops tools and frameworks, and client-oriented approach to applying technology to complex data exploitation problems.Responsibilities include but are not limited to:Develop, manage, and maintain Machine Learning infrastructure and environments.Develop ML models in cloud environments, such as Google Cloud Platform.Collaborate with data scientists on using data science and machine learning algorithms in areas such as clustering, trend analysis and anomaly detection, in accordance with industry and academic best practices.Deploy, operationalize, and scale analytic and machine learning models and solutions based on those models. Implement full life cycle of Machine Learning Operations (MLOps), collaborating with data scientists, data engineers, AI application developers, architects, security experts, and others as needed.Perform knowledge elicitation from client of business problem details and incorporate that knowledge into algorithms, models, and approaches in client solutions.Translate machine learning related technical requirements to agile tasks prioritized according to the goals and requirements of the client. Perform solution development through whiteboarding sessions with clients, partners, and team members.Contribute to solutions with machine learning techniques, MLOps practices, architecture, or other technical challenges related to machine learning engineering. Communicate findings to diverse technical and non-technical stakeholders and engage client to distill complex technical language.Minimum Qualifications:Bachelor’s degree in computer science, Engineering, or Mathematics, Applied Mathematics, Statistics, Applied Statistics, Machine Learning, Data Science, or related field and 8 years of experience OR a Master's degree and 6 years of experienceProven experience with full data-driven and AI system architecture creation, both cloud and on-prem; and with AI-related modernization and optimizationStrong experience with Machine Learning Operations (MLOps)In depth knowledge of one or more cloud providers AI/ML services (e.g., Google Cloud) and experience working across environments and on premise.Strong experience deploying and operationalizing machine learning models and solutions based on those modelsExperience engineering and deploying solutions using both conventional AI and generative AI. Experience in the full life cycle of developing a variety of types of Machine Learning models. Preferred Qualifications:Master's degree or PhD in a related field.Experience with analyzing and reporting on diverse data.Strong experience with multiple cloud platforms and with hybrid (cloud and on-premises) environmentsDeep expertise in one or more machine learning specialties.Ability to be a self-starter and take initiative. Excellent oral and written communication skills, including communicating information to a senior executive audience.Clearance Requirements:Must have active TS clearance with ability to obtain TS/SCIPhysical Requirements:Must be able to be in a stationary position more than 50% of the timeMust be able to communicate, converse, and exchange information with peers and senior personnelConstantly operates a computer and other office productivity machinery, such as a computerThe person in this position frequently communicates with co-workers, management and clients, which may involve delivering presentations. Must be able to exchange accurate information in these situationsThe person in this position needs to occasionally move about inside the office to access file cabinets, office machinery, etc.
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