AI/ML Engineer
nationsbenefits · Hyderabad, India ·
- Employment
- Full time
- Category
- ML ai
- Experience
- 4+ years
- Company size
- 51-200
- Salary
- INR 1,500,000 – 2,500,000 / year
nationsbenefits · Hyderabad, India ·
ishir · India
eProductivity Software · Whitefield, Bangalore, India
Designs and deploys AI/ML models and generative AI systems for insurance back-office modernization, using Python, MLOps, and cloud-native tools.
Job Title: AI/ML Engineer
Experience: 4-6 Years
Location: Hyderabad, India
Employment Type: Full-time
About NationsBenefits:
At NationsBenefits, we are leading the transformation of the insurance industry by developing innovative benefits management solutions. We focus on modernizing complex back-office systems to create scalable, secure, and high-performing platforms that streamline operations for our clients. As part of our strategic growth, we are focused on platform modernization — transitioning legacy systems to modern, cloud-native architectures that support the scalability, reliability, and high performance of core backoffice functions in the insurance domain.
Role Summary:
We are hiring an AI/ML Engineer with 4-6 years of hands-on experience in building and deploying AI/ML solutions.
The candidate should have strong practical exposure to model development, deployment, monitoring, and scalable AI
systems
Key Responsibilities:
• Develop and deploy AI/ML and Generative AI solutions for enterprise use cases.
• Build and maintain end-to-end ML pipelines from training to production deployment.
• Implement monitoring, observability, and performance tracking for AI systems.
• Work with APIs, vector databases, embeddings, and RAG-based applications.
• Collaborate with cross-functional teams to optimize scalable AI deployments.
Required Skills & Qualifications:
• Hands-on experience in Machine Learning, Deep Learning, and Generative AI.
• Strong Python, SQL, API development, and ML framework knowledge.
• Experience with MLOps, CI/CD pipelines, Docker, Kubernetes, and MLflow.
• Understanding of observability, monitoring, logging, and model drift detection.
• Experience with Azure Cloud Stack is a plus