Job Summary: Design, build, and deploy scalable Machine Learning models to optimize processes and enable predictive and automated capabilities across the organization. Key Responsibilities: 1. Develop and optimize Machine Learning models. 2. Implement ML solutions in production environments (MLOps). 3. Collaborate with Data Engineering, BI, and development teams. Job Objective Design, build, and deploy scalable Machine Learning models that generate value from data, optimize processes, and enable predictive and automated capabilities within the organization. Responsibilities * Develop, train, and optimize Machine Learning models. * Design data pipelines for training, validation, and deployment. * Implement ML solutions in production environments (MLOps). * Analyze large volumes of data to identify patterns and opportunities. * Collaborate with Data Engineering, BI, and development teams. * Monitor model performance and perform continuous improvements. * Automate training, evaluation, and deployment processes. * Ensure solution quality, scalability, and security. Technical Skills * **Programming languages:** Python (mandatory), SQL * **Libraries and frameworks:** * Scikit\-learn * TensorFlow * PyTorch * **Data processing:** Pandas, NumPy * **Machine Learning:** * Supervised and unsupervised models * Feature engineering * Model evaluation * **Big Data (preferred):** Spark, Hadoop * **MLOps / DevOps:** * Docker, Kubernetes * CI/CD pipelines * **Cloud (preferred):** AWS, Azure, or GCP * **Databases:** SQL and NoSQL * **APIs:** RESTful services Requirements * Bachelor’s degree in Computer Science, Data Science, Mathematics, Statistics, or related field. * 5 years of experience in Machine Learning. * Experience developing and deploying models into production. * Strong knowledge of statistics and algorithms. * Experience in data manipulation and analysis. Employment type: Full-time Salary: $35,000.00 \- $40,000.00 per month Work location: On-site