Roles & Responsibilities
· Apply machine learning, generative AI and big data to build, manage and automate applications and pipelines for analytics platform
· Design and develop ML Ops platform for the future requirements of the business, with fairness and robustness in mind
· Implement and apply industry standard ML solutions to solve real world challenges
· Study and evaluate the state-of-the-art technologies, tools, and frameworks of machine learning engineering, and establish, apply and maintain best practices and principles of machine learning
· Perform code optimization, code reviews to improve the quality of work
· Automate software testing by writing unit tests for all production code
· Manage available resources such as hardware, data, and personnel so that deadlines are met
· Work with different stakeholders to ensure that the bank’s production release process is adhered to


Requirements
· Bachelor’s or master’s degree in software engineering, computer science or related fields
· 4+ years of experience in industry (ideally banking) with demonstrated track record of application development in advanced analytics and machine learning to achieve business impact.
· Excellent understanding of software engineering principles and design patterns.
· Excellent programming skills in Python (preferably scikit-learn, FastAPI & Strawberry) and willingness to learn other languages as required by the project.
· Good knowledge on SQL, joining and worked on database like MySQL or Oracle or any other related database.
· Good knowledge on working with tools such as JIRA, Git and Jenkins.
· Experience in working with Agile software development ecosystem.
· Preferably experience with PCF and AWS SageMaker.
· Good to have experience in PySpark and knowledge of BigData ecosystem.
· Strong in problem-solving, being resourceful with end to end critical thinking to find out solutions even in unfamiliar scenarios.
· Good communication and project management skills.
· Strong interests in learning about recent developments in machine learning through own initiatives.