Senior Full-Stack Machine Learning Engineer - Java/Kotlin

Job Role : Sr Full-Stack Machine Learning Engineer

Exp Level : 3 to 5 Years

Location : Pune/Indore

Budget : 12 to 18 LPA

Notice Period : Immediate 15 Days

Key Responsibilities:

•ML solutions: Develop and deploy predictive models for risk scoring, claims automation, fraud detection,

and personalization.

•Backend services: Build robust APIs using Java/Kotlin (Spring Boot or Ktor) for model inference and

integration with insurance platforms.

•Data pipelines: Design and optimize ETL/ML workflows in Databricks or Spark, ensuring compliance with

data governance and regulatory standards.

•Frontend: Create intuitive React.js dashboards for underwriters, claims teams, and business users to visualize

model outputs and KPIs.

•Database management: Work with PostgreSQL databases to store policy, claims, and model metadata

securely.

•Model deployment & monitoring: Implement production-grade deployment strategies with drift detection,

audit trails, and rollback mechanisms.

•Compliance & security: Ensure solutions adhere to insurance regulations (e.g., MAS, GDPR) and internal

security policies.

•Cross-functional collaboration: Communicate effectively with actuaries, data scientists, and business

stakeholders.

Amplify Health confidential and proprietary information. Do not distribute.

Required Qualifications:

•3–5 years of experience in ML engineering with exposure to insurance or financial services preferred.

•Strong programming skills in Java or Kotlin; experience with Spring Boot/Ktor for API development.

•Hands-on with Databricks and Spark for large-scale data processing.

•Proficient in React.js for building user interfaces.

•Solid understanding of SQL and data modeling for transactional and analytical systems.

•Experience deploying ML models in production with monitoring and governance.

•Excellent communication skills to explain technical concepts to non-technical teams.

Nice-to-Have:

•Knowledge of insurance workflows (claims, fraud detection).

•Familiarity with regulatory compliance frameworks (GDPR, MAS guidelines).

•Experience with MLflow, feature stores, and model explainability tools.

•Exposure to cloud platforms (AWS/Azure/GCP) and containerization (Docker/Kubernetes).

Suitable candidates can also apply at : naresh@uniwavesoft.com