ML Application Development: Develop, test, and maintain high-quality ML-based software applications using Python, Machine Learning libraries, Typescript, Web frameworks like React, and other relevant technologies.
Scalable Solutions: Design and implement scalable and efficient solutions on AWS, ensuring robust performance and security.
Data-Driven Decision Making: Support data-driven decision making by using Prefect for workflow orchestration and SQL, Snowflake for data warehousing.
Model Development: Develop and deploy machine learning models using Python and relevant libraries/frameworks.
Integration: Integrate machine learning solutions with existing data pipelines and DevOps practices.
Production Management: Manage production-level code and ensure the reliability of machine learning models in a live environment.
Containerization: Utilize Docker and Kubernetes for containerization and orchestration of applications.
Collaboration: Collaborate with cross-functional teams to capture requirements, design solutions, and ensure successful project delivery.
Support and Troubleshooting: Provide production support, troubleshoot issues, and implement fixes to ensure the smooth operation of software applications.
Code Reviews and Best Practices: Participate in code reviews, contribute to standard methodologies, and continuously improve the development process.
Industry Trends: Stay updated with the latest industry trends and technologies to ensure our solutions remain at the forefront of innovation.