Senior Machine Learning Engineer

Company Description Rhombus Power Inc. provides AI-powered predictive decision support that helps organizations make better decisions in real time. Its platform unifies multi-domain data, advanced AI modeling, and human expertise to deliver actionable insights at speed and scale. Rhombus Power primarily supports U.S. Government leaders and international partners with mission-critical analytics. Team members work on impactful problems where technology directly informs high-stakes decisions. The company fosters a collaborative environment focused on innovation, reliability, and measurable outcomes.Role Description This is a full-time, on-site Machine Learning Engineer role based in Palo Alto, CA. The Machine Learning Engineer will design, implement, and deploy machine learning models that power predictive decision support across diverse problem sets. Daily responsibilities include exploring and preprocessing complex datasets, selecting and training multi-modal deep learning and language models, and focusing specifically on large-scale optimization across different hardware configurations including edge. The role involves collaborating closely with data scientists, software engineers, and domain experts to translate operational needs into production-ready ML solutions. The Machine Learning Engineer will also contribute to code reviews, experiment tracking, model evaluation, and continuous improvement of ML pipelines and infrastructure.QualificationsStrong foundation in Computer Science, including data structures, Algorithms, and software engineering best practices.Experience with Statistics and Pattern Recognition for building, evaluating, and interpreting predictive models.Hands-on expertise with Deep Neural Networks, Language Models and modern machine learning frameworks (e.g., TensorFlow, PyTorch, or similar).Proficiency in one or more programming languages commonly used in ML (such as Python, Java, or C++), and experience with version control tools.Familiarity with end-to-end ML workflows, including data preprocessing, feature engineering, model training, validation, and deployment.Bachelor’s or higher degree in Computer Science, Electrical Engineering, Mathematics, or a related technical field, or equivalent practical experience.Ability to work on-site in Palo Alto, CA, collaborate effectively in cross-functional teams, and communicate technical concepts clearly to diverse stakeholders.Experience with cloud platforms, ML ops tools, or large-scale data processing (e.g., Kubernetes, Docker, Spark, or similar) is a plus.Background in applied ML for high-impact or security-focused domains, or experience working with government or enterprise customers, is beneficial.