Develop and optimize machine learning models for various applications. Preprocess and analyze large datasets to extract meaningful insights. Deploy ML solutions into production environments using appropriate tools and frameworks. Collaborate with cross-functional teams to integrate ML models into products and services. Monitor and evaluate the performance of deployed models. Minimum of 5 years of relevant work experience and a Bachelor's degree or equivalent experience. Experience with ML frameworks like TensorFlow, PyTorch, or scikit-learn. Familiarity with cloud platforms (AWS, Azure, GCP) and tools for data processing and model deployment. Several years of experience in designing, implementing, and deploying machine learning models. MSc or equivalent experience in a quantitative field (Computer Science, Mathematics, Engineering, Artificial Intelligence, etc.) or a bachelor's degree in engineering, science, statistics or mathematics with a strong technical background in machine learning. Hands-on experience with Python or Java, along with relevant technologies such as Spark, Hadoop, Big-Query, SQL, is required. Candidates must possess a comprehensive understanding of machine learning algorithms and explainable AI techniques. Additionally, expertise in at least one of the following specialized areas is required: Computer Vision, Graph Mining, Natural Language Processing (NLP), or Generative AI (GenAI). Experience with Cloud frameworks such as GCP, AWS is preferred. Experience with developing machine learning models at scale from inception to business impact Experience in designing ML pipelines, including model versioning, model deployment, model testing, and monitoring Experience in mentoring and supporting junior data scientists or engineers. Experience working in a multi-cultural and multi-location organization - an advantage. Team player, responsible, delivery-oriented, details-oriented, outstanding communication skills.