ML Engineer

As a Machine Learning Engineer at our company, you will play a crucial role in developing and implementing machine learning models to address real-world challenges and enhance business outcomes. By collaborating closely with data scientists, software engineers, and product managers, you will contribute to designing, constructing, and deploying innovative solutions. Key Responsibilities: - Design, develop, and implement machine learning models for diverse applications such as predictions, customer churn analysis, and fraud detection. - Collect, clean, and preprocess large datasets to facilitate training and evaluation processes. - Conduct exploratory data analysis and feature engineering to enhance model performance. - Evaluate and choose suitable machine learning algorithms and techniques based on business needs and data characteristics. - Develop and manage machine learning pipelines for data ingestion, preprocessing, training, and deployment. - Monitor and optimize the performance of deployed models in production environments. - Stay updated on the latest advancements in machine learning and related technologies. - Collaborate with cross-functional teams to integrate machine learning solutions into existing systems. - Communicate technical concepts and findings effectively to both technical and non-technical audiences. - Mentor and guide junior data scientists to foster a collaborative and knowledge-sharing environment. Qualifications Required: - Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or a related field. - 2 to 3 years of experience in developing and deploying machine learning models in a professional setting. - Strong understanding of machine learning algorithms and techniques, including supervised, unsupervised, and reinforcement learning. - Proficiency in Python and relevant machine learning libraries such as scikit-learn, TensorFlow, PyTorch. - Familiarity with cloud computing platforms (e.g., AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes). - Experience in building and deploying models using Python Azure Data Factory (ADF), Azure Databricks, PySpark, Delta Lake, ETL/ELT, data pipelines, data lakehouse architecture. - Excellent problem-solving, analytical, communication, and collaboration skills. - Telecom industry experience is highly preferred. As a member of our team, you will benefit from a culture of caring, continuous learning and development opportunities, engaging and impactful work, balance and flexibility, and a high-trust environment. GlobalLogic, a Hitachi Group Company, is dedicated to partnering with leading companies worldwide in creating intelligent products, platforms, and services to drive digital transformation.,