Job Summary: Client is seeking a highly skilled and talented Machine Learning Engineer to join our innovative team. In this role, you will apply your expertise in machine learning and data analysis techniques to develop and deploy cutting-edge models and algorithms that enable us to extract valuable insights from complex and diverse data sources. As a Machine Learning Engineer, you will play a pivotal role in driving client's digital transformation, helping shape the future of renewable energy, sustainability, and clean technology. Responsibilities: closely with cross-functional teams, including data scientists, engineers, and subject matter experts to identify and understand business problems and define project goals and requirements. develop, train, and deploy machine learning models and algorithms to solve business challenges and optimize operational processes. with Software Engineers and Data Scientists to integrate machine learning models into production systems and ensure scalability, reliability, and performance. This includes containerizing applications and automating deploying and testing to AWS or on-premise data center servers. data exploration and pre-processing tasks to ensure data quality and suitability for machine learning tasks. and implement data visualization techniques to effectively communicate complex insights and model outputs to stakeholders. and benchmark different machine learning algorithms and techniques to identify the best approaches for specific use cases. in end-to-end model development, including data preparation, feature engineering, model selection, hyperparameter tuning, training, and iterative improvement. up-to-date with the latest advancements in machine learning, artificial intelligence, and related fields, and explore opportunities to leverage emerging technologies within Client. Qualifications: or advanced degree in Computer Science, Data Science, Statistics, or a related field. experience working as a Machine Learning Engineer or Sr. Developer working in Data Science, in a professional setting. proficiency in programming languages such as Python (Java optional), as well as experience with machine learning libraries/frameworks (e.g., TensorFlow, PyTorch, scikit-learn). mathematical and statistical foundations, with knowledge of algorithms, data structures, and optimization techniques. with big data technologies (e.g., Spark, Kafka) and working with large-scale datasets. problem-solving skills and the ability to apply critical thinking to understand complex problems and develop innovative solutions. communication and teamwork skills, with the ability to effectively collaborate with cross-functional teams and present technical ideas to non-technical stakeholders. with cloud platforms and services (e.g., AWS, Azure, GCP) is a plus. with renewable energy, power systems, or utilities industry is a plus. passion for renewable energy, sustainability, and the pursuit of clean technology solutions.
