About Epirus Epirus is a high-growth technology company dedicated to overcoming the asymmetric challenges inherent to the future of national security. Epirus' flagship product, Leonidas, is a software-defined system built using intelligent power management techniques which allow power-hungry systems to do more with less. Job Summary: Join our team to pioneer cutting-edge machine learning and deep learning solutions that will revolutionize the future of advanced electronic systems. In this role, you will tackle complex challenges in AI-driven power management, digital twin simulations, and multi-domain data analysis, driving next-generation innovation. Collaborating with world-class engineers and researchers, you will develop intelligent models that push the boundaries of real-time decision-making and electronic system intelligence. By leveraging state-of-the-art deep learning architectures and advanced optimization techniques, you will shape the future of high-performance electronic systems and intelligent automation. Responsibilities: * Develop and deploy models to optimize performance, automation, and intelligence in next-generation electronic systems, including intelligent power management and real-time decision-making in embedded systems. * Develop and implement data processing techniques to enhance data quality in advanced electronic applications. * Apply machine learning models to digital twin simulations for real-time predictive analytics and performance optimization of advanced electronic systems. * Collaborate with System Engineers in a laboratory environment to develop and refine data collection pipelines and frameworks for training AI models. * Work closely with cross-functional teams (e.g., software engineers, hardware developers, researchers) to integrate deep learning models into production environments. * Develop intuitive visualization tools to facilitate AI-assisted decision-making for stakeholders. * Deploy machine learning models on cloud and edge computing platforms to enable real-time AI processing in distributed systems. * Stay ahead of emerging AI trends and advancements, continuously refining methodologies to enhance system intelligence and innovation. Basic Qualifications: * Bachelor's degree in Electrical Engineering, Computer Science, Mathematics, Statistics, Physics, or a related technical field. * Strong foundation in machine learning theory and practice, including architecture selection, feature engineering, training, validation, optimization, and deployment. * Understanding of deep learning architectures, such as CNNs, RNNs, Transformers, and GANs, and their application in signal processing, pattern recognition, and optimization. * Proficiency in Python programming, with experience in scientific computing libraries such as NumPy, Pandas, Matplotlib, and SciPy for data analysis and visualization. * Hands-on experience with one or more ML frameworks, including TensorFlow, PyTorch, Keras, and/or Scikit-learn for deep learning and machine learning model development. * Working knowledge of computer science fundamentals, including algorithms, data structures, object-oriented programming (OOP), and software development best practices. * Experience working in collaborative, cross-functional environments, engaging with systems engineers, physicists, and software developers to integrate AI solutions into electronic systems. * The ability to obtain and maintain a U.S. government-issued security clearance is required. U.S. citizenship is required, as only U.S. citizens are eligible for a security clearance. Preferred Skills and Experience: * Master's or Ph.D. in a related field with research experience in machine learning for electromagnetic modeling, power management, or digital twin simulations. * Basic knowledge of RF systems and testing equipment, such as oscilloscopes, spectrum analyzers, vector network analyzers, and RF amplifiers to support AI-driven signal processing applications. * Experience with optimization techniques (e.g., genetic algorithms, reinforcement learning, convex optimization, Bayesian methods) for real-time control and AI-driven system enhancements. * Familiarity with digital twin simulation concepts, including real-time predictive modeling and AI-driven system optimizations. * Knowledge of Linux-based systems and communication with in-house clusters. * Experience with cloud computing platforms (AWS, Azure, or GCP) and edge computing for AI deployment in real-time embedded systems. * Contributions to machine learning research (published papers, patents, open-source contributions) in relevant fields. ITAR REQUIREMENTS: * To conform to U.S. Government space technology export regulations, including the International Traffic in Arms Regulations (ITAR) you must be a U.S. citizen, lawful permanent resident of the U.S., protected individual as defined by 8 U.S.C. 1324b(a)(3), or eligible to obtain the required authorizations from the U.S. Department of State. Learn more about the ITAR here. At Epirus, you'll work with technical peers and great people-and get first crack at some of the defining technology challenges of our time. Here, "impossible" is just a challenge. We're a diverse, fast-growing team of change-makers fueling the future of energy with revolutionary solutions. Join us and rewrite the rules.