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NationsBenefits

AI/ML Engineer

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In-Office
Hyderabad, Telangana, IND
Mid level
In-Office
Hyderabad, Telangana, IND
Mid level
Design, build, and deploy AI/ML and Generative AI solutions for enterprise use cases. Build and maintain end-to-end ML pipelines, deploy models to production, and implement monitoring, observability, and model-drift detection. Work with APIs, vector databases, embeddings, and RAG-based applications, and collaborate with cross-functional teams to optimize scalable AI deployments.
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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

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