Key Deliverables :
- Plan, design, implement, and test Python APIs, algorithms, and examples for predictive modeling lifecycle.
- Work with data scientists, QA engineers, and UX designers to create efficient pipelines for training and testing machine learning models.
- Design and create reusable Python API packages for data science teams.
- Engage with internal users, clients, and pre-sales engineers to design proofs of value, demonstrations, and educational materials.
Role Responsibilities :
Collaborate with cross-functional teams to implement predictive modeling solutions and operationalize machine learning models.Work on software development methodologies, including architecture, performance tuning, and debugging.Contribute to ML operations and utilize Python ML packages for model deployment and monitoring.Leverage tools such as Java, Kafka, Spring Boot, Kubernetes, and Helm to support data science solutions.Skills Required
Java, Kafka, Api, Python, Kubernetes