Machine Learning Engineer

Join Our Team as a Machine Learning Engineer!

Are you a talented and enthusiastic Machine Learning Engineer looking for an exciting opportunity? Join our Machine Learning Operations team and be at the forefront of designing, building, testing, deploying, and monitoring cutting-edge machine learning and analytics applications. This role offers the chance to work with state-of-the-art technologies and contribute to the automation of machine learning and AI use cases. Collaborate with data scientists, actuaries, data engineers, and other software engineers to help architect our banks modern Machine Learning ecosystem.

Key Responsibilities:

Machine Learning Automation and Software Engineering:

• Design, build, and deploy machine learning and analytics automation processes.
• Refactor existing code bases to enhance efficiency, robustness, scalability, and automation of machine learning workflows.

Cloud-Native Development:

• Utilize Databricks and Azure for data engineering and machine learning use cases.
• Leverage Azure services such as Azure Functions, CosmosDB, API Gateway, and Azure Machine Learning to build intelligent data applications.

DevOps and Software Engineering:

• Build CI/CD pipelines to improve development and deployment practices.
• Develop robust testing and monitoring capabilities for machine learning and AI use cases.
• Experience with Git, Jenkins, Azure DevOps, and Terraform is advantageous.
• Build APIs to serve machine learning models.
• Apply software engineering best practices to develop robust, scalable, and maintainable code.
• Create microservice applications using Docker and container orchestration tools like OpenShift.
• Collaborate with cross-functional teams to deliver high-quality software solutions for machine learning and data use cases.
• Create and maintain documentation of processes, technologies, and code bases.

Machine Learning Frameworks:

• Familiarity with MLFlow, PyTorch, TensorFlow, etc., is beneficial for the productionization of machine learning use cases.

Collaboration:

• Work closely with data scientists, actuaries, data engineers, and other software engineers to understand and address their data needs.
• Contribute actively to the architecting of our banks modern Machine Learning data ecosystem.

Requirements Education and Experience:

• 1-3 years of experience as a Software Engineer.
• Bachelors degree in engineering or a related field. Other qualifications will be considered if accompanied by sufficient experience in software engineering.

Technical Skills:

• 2 years of experience using Python and SQL.
• Exposure to Linux shell scripting is advantageous.
• Experience with Spark is advantageous.
• Interest in software architecture.
• Knowledge of cloud compute services.
• Familiarity with serverless computing and cloud-native development.
• Keen interest in systems design and software architecture.
• Knowledge of machine learning frameworks/packages (e.g., MLFlow, Spark ML, Sklearn).
• Understanding of CI/CD concepts and API development, with implementation experience being advantageous.
• Strong critical thinking, problem-solving, and collaboration skills.
• Ability to collaborate with cross-functional tech teams as well as business/product teams.
• Excellent communication skills.
• Commitment to excellence and high-quality delivery.
• Passion for personal development and growth, with a high learning potential.

If youre passionate about machine learning and eager to work in a dynamic and innovative environment, wed love to hear from you! Apply now and be part of our journey to revolutionize the banking industry with cutting-edge AI and machine learning solutions.