AI/ML Engineer/Data Scientist

Job Title: AI/ML Engineer/Data Scientist Role Overview We are looking for an experienced Full Stack Data Scientist who can take AI and machine learning initiatives from concept to production. The role requires someone who can understand business challenges, design suitable analytical and ML solutions, develop reliable models, and support their deployment into scalable production environments. The ideal candidate should be comfortable working across data science, software engineering, cloud platforms, and MLOps. This position is best suited for someone who not only builds accurate models but also ensures that those models are usable, maintainable, monitored, and effective in real-world business operations. Responsibilities • Understand business objectives and convert them into practical AI, machine learning, and analytics solutions. • Design, build, test, validate, and document machine learning models and AI-driven applications. • Develop robust Python-based workflows for data preparation, feature creation, model training, scoring, and inference. • Build batch and real-time ML applications, APIs, or services as required by the business use case. • Write clean, reusable, and production-quality code following software engineering standards. • Apply best practices such as modular development, unit testing, code review, version control, and CI/CD. • Work closely with data engineering, cloud, and MLOps teams to deploy and manage ML solutions in production. • Support model tracking, versioning, monitoring, retraining, and performance management. • Monitor model accuracy, data quality, drift, stability, and production behavior. • Prepare technical documentation required for model governance, validation, audit, and operational support. • Partner with business and technology stakeholders to ensure AI/ML solutions are scalable, reliable, and aligned with business goals. Required Skills and Experience • 6+ years of hands-on experience in data science, machine learning, applied analytics, or AI solution development. • Strong experience building models and applications that solve practical business problems. • Experience supporting ML solutions beyond development, including deployment, monitoring, and production support. • Strong knowledge of statistical modeling, machine learning algorithms, AI techniques, and applied data analysis. • Advanced Python programming skills with experience in libraries such as pandas, NumPy, scikit-learn, TensorFlow, or similar frameworks. • Strong SQL skills and experience working with large datasets. • Experience with big data or distributed processing tools such as PySpark. • Ability to develop maintainable, scalable, and well-structured code for production environments. • Experience with AWS-based data science and ML services such as SageMaker, S3, Redshift, MLflow, and compute services. • Good understanding of MLOps concepts, including deployment pipelines, model registry, monitoring, retraining, and lifecycle management. • Strong analytical thinking, problem-solving ability, and communication skills. Education Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, Engineering, Mathematics, or a related quantitative discipline.