ML Engineer

We are seeking an experienced professional for this opening. Key Responsibilities: - Design, build, and optimize data and ML pipelines for training and inference. - Develop and deploy scalable, production-ready machine learning models and systems. - Manage infrastructure for model serving, monitoring, and performance optimization. - Clean, validate, and preprocess data to ensure high quality and integrity. - Translate data science prototypes into robust production code and services. - Research, select, and implement appropriate ML algorithms and tools for business needs. - Train, retrain, fine-tune, and evaluate models to maintain accuracy and reliability. - Perform statistical analysis and testing to improve model performance. - Collaborate closely with Data Engineers, Data Scientists, and Software Engineers to integrate ML solutions. - Document ML system design, development processes, and operational workflows. Requirements: - Bachelor's degree in Computer Science, Data Science, or a related field, with 2-3 years of hands-on experience in machine learning, data science, or applied Al. - Strong programming skills in Python and experience working with ML frameworks such as Scikit-learn, TensorFlow, or PyTorch. - Experience deploying machine learning models into production, including APIs, dashboards, or integrated systems, with familiarity in MLOps tools and workflows. - Working knowledge of SQL, database design, ETL pipelines, Docker, Git, and data visualization tools. - Exposure to financial inclusion or small enterprise data, with an interest in ethical, explainable Al and social impact analytics.