Overview:

• We are seeking a skilled Machine Learning Engineer to join our team and help transform and modernize critical data science models from legacy code and systems to modern cloud-based solutions using Python, AWS SageMaker, and Snowflake.

• We are looking for a candidate who excels in writing high-quality Python code that adheres to industry and internal coding standards and is proficient with our modern tech stack.
• In addition to development, a key focus of this role will be designing and implementing comprehensive testing strategies, including unit, integration, and end-to-end tests. Additional responsibilities will include helping to build, release, and maintain model pipelines and model APIs.
• This will involve working with our cloud tech stack, CI/CD pipelines, and containers, and collaborating with data scientists, machine learning engineers, DevOps, and InfoSec teams to deploy new projects and ensure the success of model releases and retraining activities.

• Transform legacy code into robust, high-quality Python code that complies with internal coding standards and includes comprehensive test coverage
• Work with the machine learning engineering team to develop and implement robust testing strategies, including unit, integration, and end-to-end tests
• Build a maintain scalable machine learning pipelines on AWS cloud platforms using SageMaker and Snowflake
• Assist in deploying machine learning models into production environments, ensuring scalability, reliability, and performance
• Maintain and monitor existing pipelines and model APIs to ensure optimal functionality
• Work closely with data scientists, machine learning engineers, DevOps and InfoSec teams to initiate and manage various releases
• Translate business requirements into technical solutions through effective communication
• Translate technical project details into clear documentation and intuitive diagrams that help integrate information flows with upstream and down stream teams.

• Highest degree specifically in: Statistics, Mathematics, Physics, Engineering, Computer Science, Economics / Econometrics, Finance, Data Science, Machine Learning, AI, Financial Engineering, Computational Finance, Operational Research, Industrial Engineering.
• Active AWS Solutions Architect Associate certification
• Experience with SAS (statistical analysis) programming language
• Experience working with API frameworks (Flask, FastAPI) and  SageMaker
• Ability to design and implement comprehensive testing strategies.