SwRI's Defense & Intelligence Solutions / RF Sensors and Systems Department presents an unparalleled opportunity for Principal Machine Learning Operations (MLOps) position to engage in some of the most stimulating and impactful work that combines both MLOps and DevOps focused on data engineering, ML model development, and systems engineering for real-world application. We are actively seeking dynamic MLOps who are passionate about taking on the most challenging projects in data analytics, Artificial Intelligence (AI), and Machine Learning (ML).

• Lead MLOps focused on ML and DevOps focused on data engineering, analytics, AI & ML model creation, and AI/ML embedded system architecture. Manage prototyping, testing, and documentation processes, driving innovation in AI/ML for national defense.
• Collaborate with the engineering team to design, develop, test, and document automated analysis and reporting features for applications, focusing on integrating AI/ML models into information exploitation systems. This includes field implementation of these advanced capabilities.
• Lead development using knowledge and data engineering and data analytics to apply new technologies, skills, techniques, and advancement of AI/ML in new areas and new technologies.
• ML and signal processing would involve some deep learning models for signal classification.
• Join elite engineers in tackling complex projects in knowledge/information exploitation, spectrum exploitation, and data engineering.
• Deliver impactful results for a diverse client base, contributing to innovative engineering solutions.
• Collaborate with clients and analysts to identify AI/ML needs and integrate these technologies into broader systems.
• Work across the Division to enhance AI/ML development capabilities, shaping system architectures and expanding tech horizons.

• Develop processes, methods, standards and procedures and perform data analytics of small and large volumes of highly interesting technical data.
• Identify and discover data analytics and AI/ML requirements, design architectures for the deployment of AI/ML in research-oriented and production systems; design knowledge maintenance and management capabilities for these systems.
• Lead data analysts and engineers in the design, development and performance accuracy tuning of AI algorithms and ML models. Lead continuous development/integration to include verification, validation and documentation in DEVOPS environments.
• Lead senior engineers and data analysts with identifying metrics for benchmarking and optimization, prototype experimentation, testing, and troubleshooting, and integration into larger information systems hosting the AI/ML components.
• Interface with clients and clients' data analysts to define AI/ML needs and requirements; and work within the RSD Department and D&IS Division to help expand AI/ML development capabilities as institutional knowledge and skills.

• Requires a Bachelors, Masters or a PhD in Machine Learning/Artificial Intelligence, Data Science, Data Engineering, Computer Engineering.
• Must hold active TS/SCI clearance.
• 12 years: Data Engineering, to include data analytics, AI & ML model development using a variety of AI and neural network techniques and approaches.
• Python, TensorFlow, Keras, pytorch, and/or other development and data analysis tools. C and Java are desired. Knowledge of MATLAB for data engineering desired but not required.
• Design and planning of data architectures leading to AI and ML integration into large application systems.
• AWS AI and ML development desired, but not required. Knowledge of the Intelligent Community Classified Cloud a plus, but not required.
• A valid/clear driver's license is required.

Applicant selected will be subject to a government security investigation and must meet eligibility requirements for access to classified information. Applicant must be a U.S. citizen.

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An Equal Employment Opportunity/Affirmative Action Employer
Race/Color/Religion/Sex/Sexual Orientation/Gender Identity/National Origin/Disabled/Veteran
Committed to Diversity in the Workplace

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