Machine Learning Engineer

The Machine Learning Engineer will lead the development of advanced Machine Learning and Artificial Intelligence solutions that support large-scale business applications and customer experiences. The role will involve designing scalable data pipelines using PySpark, developing and deploying production-grade machine learning models using TensorFlow or PyTorch, and translating complex business challenges into data-driven solutions. The ideal candidate will have strong expertise in supervised and unsupervised learning, deep learning architectures, cloud-based machine learning platforms, and production model deployment, while also contributing to technical leadership and mentoring. Key Responsibilities Lead the development of advanced Machine Learning and Artificial Intelligence solutions. Design and develop scalable data pipelines using PySpark. Develop, train, validate, and deploy production-grade machine learning models. Utilize TensorFlow and/or PyTorch for deep learning model development. Apply supervised and unsupervised machine learning techniques to solve complex business problems. Design and implement deep learning architectures, including CNN, RNN, and LSTM models. Develop and optimize machine learning solutions using Scikit-Learn. Deploy and manage machine learning models using AWS cloud technologies and SageMaker. Translate complex business challenges into scalable, data-driven machine learning solutions. Collaborate with data scientists, engineers, and business stakeholders to define and deliver ML/AI initiatives. Develop production-ready ML solutions with a focus on scalability, reliability, and performance. Mentor team members and contribute technical expertise to strategic data and AI initiatives. Stay current with emerging Machine Learning and Artificial Intelligence technologies and practices. Required Qualifications Strong hands-on experience with Python. Strong experience with PySpark. Hands-on experience with TensorFlow and/or PyTorch. Experience with Scikit-Learn. Strong experience with AWS and cloud-based machine learning solutions. Experience with ML model development and deployment. Strong understanding of supervised and unsupervised learning. Experience with deep learning architectures such as CNN, RNN, and LSTM. Experience developing and deploying production-grade machine learning models. Strong analytical, problem-solving, and technical leadership skills. #J-18808-Ljbffr Compunnel, Inc.