Machine Learning Engineer

Position Overview:  

We are seeking an experienced Machine Learning Engineer to join our Enterprise AI Enablement team. In this role, you will collaborate with cross-functional teams to transform business challenges into ML-powered solutions. You will be responsible for the end-to-end development of machine learning projects, from conceptualization to deployment and maintenance. This position offers the opportunity to work on diverse projects across enterprise business units while building scalable ML solutions. 

Key Responsibilities: 

• Design and implement machine learning solutions that address complex business problems across different enterprise business units 

• Collaborate with business stakeholders to understand requirements and translate them into technical specifications 

• Create robust prototypes to validate AI concepts and transform them into production-ready systems 

• Design, develop and deploy end-to-end MLOps pipelines, including data preprocessing, hyper parameter tuning, model training, evaluation, and production deployment 

• Implement best practices for model monitoring, maintenance, and performance optimization 

• Conduct thorough testing and validation of ML models to meet the standards performance KPI metrics to ensure reliability and accuracy 

• Document technical processes, methodologies, model governance, and model architectures 

Required Qualifications: 

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field. A Ph.D. is a plus. 

• Minimum 5 years of professional experience in machine learning engineering 

• Experience with the Infrastructure Sizing, Cost Management, Budget Forecasting and Reporting, and Workflow Optimization 

• Strong programming skills in Python and experience with ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn) 

• Proven experience in developing and deploying production grade ML models in both conventional and deep learning techniques 

• Proficiency in data preprocessing, feature engineering, and model evaluation techniques 

• Experience with version control systems (e.g., Git) and ML experiment tracking tools 

• Strong understanding of statistical analysis and machine learning algorithms 

• Excellent problem-solving, analytical skills, and strong communication skills 

Preferred Qualifications: 

• Ph.D. in Computer Science, Machine Learning, or a related field 

• Experience with forecasting models and time series analysis, preferably in manufacturing and supply chain domains 

• Expertise in anomaly detection algorithms and implementation 

• Knowledge of cloud platforms (AWS, Azure, or GCP) and their ML services 

• Experience with ML frameworks, tools and practices 

• Familiarity with distributed computing and big data technologies 

• Knowledge of containerization (Docker) and orchestration (Kubernetes) 

• Experience with CI/CD pipelines for ML applications 

• Contributions to open-source ML projects or research publications