Machine Learning Engineer II

**Position Overview:** We are seeking an experienced Machine Learning Engineer II to join our team and take a leading role in the development of machine learning algorithms for RF signal classification. The successful candidate will have a strong background in machine learning and signal processing, with a passion for applying cutting-edge techniques to geospatia satellite information systems. **Responsibilities:** * Lead the design, implementation, and optimization of machine learning algorithms and models for RF signal classification, leveraging techniques such as deep learning, feature engineering, and anomaly detection. * Collaborate with cross-functional teams to understand the requirements and constraints of satellite payloads, and translate them into effective ML solutions. * Conduct research and experimentation to explore new approaches and algorithms for improving the accuracy and efficiency of signal classification in satellite communication systems. * Work closely with hardware engineers to optimize ML models for deployment on embedded hardware payloads, considering factors such as computational resources, power consumption, and memory constraints. * Lead performance analysis and debugging efforts to identify and address issues related to model inference, execution, and integration with embedded systems. * Mentor junior ML engineers and contribute to the technical growth and development of the team. **Requirements:** * 3+ years of experience in machine learning, with a focus on signal processing, classification, and anomaly detection. * Proficiency in programming languages such as Python, with hands-on experience in ML frameworks (e.g., TensorFlow, PyTorch). * Strong understanding of machine learning fundamentals, algorithms, and techniques. * Experience with data preprocessing, feature engineering, and model evaluation in the context of satellite communication systems. * Familiarity with embedded systems development and hardware-software co-design principles is a plus. * Excellent problem-solving skills and ability to work in a fast-paced startup environment. * Strong communication and leadership skills. **Preferred Qualifications:** * Experience with Geospatial data and RF signal processing. * Knowledge of digital signal processing techniques and algorithms. * Familiarity with software development tools and version control systems (e.g., Git). * Publications or contributions to the machine learning community.