Responsibilities

• Design, build, test, and maintain production-grade backend services and APIs using Python and Java.
• Integrate machine learning models and analytical components into real-time and batch software workflows.
• Develop reusable application components for feature calculation, inference, decision support, and model output interpretation.
• Build internal and customer-facing tools that help users explore, evaluate, and understand analytical outcomes.
• Apply sound software engineering practices, including modular design, code review, automated testing, documentation, and continuous improvement.
• Improve system performance, reliability, security, observability, and maintainability across the software lifecycle.
• Work with data scientists to translate prototypes and research outputs into robust, well-defined product capabilities.
• Participate in delivery and operational ownership for the services you build, including deployment, incident analysis, and remediation.

Requirements

• Professional software engineering experience with a strong record of delivering production systems.
• Strong programming skills in Python and Java, including object-oriented design, clean interfaces, and maintainable application structure.
• Experience designing and developing APIs, backend services, distributed systems, or data-intensive applications.
• Solid understanding of software testing, version control, code review, CI/CD, secure development, and production support.
• Practical experience integrating machine learning models, statistical algorithms, or advanced analytics into software products.
• Ability to work with data stores and data platforms such as Snowflake, relational databases, or comparable technologies.
• Understanding of common machine learning concepts, feature engineering, inference, evaluation, and the limitations of analytical systems.
• Strong ownership, problem-solving, and communication skills, with the ability to execute independently and collaborate across disciplines.