Senior AI/ML Engineer

NB Healthcare Technologies; Hyderabad; On-site; INR 1,800,000 - 3,000,000; Full time

Job summary

NB Healthcare Technologies in Hyderabad is seeking an experienced AI/ML lead to drive enterprise-grade AI/ML and Generative AI initiatives. You will spearhead design, development, and deployment of scalable pipelines and governance frameworks to support production systems.

You will mentor teams, collaborate with stakeholders, and optimize AI architectures for performance, cost, and reliability while maintaining robust observability and CI/CD practices.

Qualifications

• Strong hands-on experience in Artificial Intelligence, Machine Learning, and Generative AI systems.
• End-to-end ML lifecycle: data ingestion, feature engineering, model development, validation, deployment, monitoring, and retraining.

Responsibilities

• Lead development and deployment of enterprise-scale AI/ML and Generative AI solutions.
• Build and optimize end-to-end ML pipelines including experimentation, deployment, monitoring, and retraining.
• Develop scalable inference architectures, vector search systems, and RAG-based applications.
• Implement observability, monitoring, governance, and production support mechanisms for AI systems.
• Drive model lifecycle management including versioning, experimentation tracking, and CI/CD automation.
• Mentor engineering teams and establish AI/ML engineering best practices.
• Collaborate with business stakeholders to identify and implement AI-driven solutions.
• Optimize AI systems for scalability, latency, reliability, and cost efficiency.

Skills

AI/ML expertise

Generative AI

Python

SQL

APIs

LangChain

Hugging Face

Vector databases

RAG pipelines

MLOps

CI/CD

Kubernetes

Observability

Tools

MLflow

DVC

Docker

Kubernetes

Azure

Job description

Key Responsibilities

• Lead development and deployment of enterprise-scale AI/ML and Generative AI solutions.


• Build and optimize end-to-end ML pipelines including experimentation, deployment, monitoring, and retraining.


• Develop scalable inference architectures, vector search systems, and RAG-based applications.


• Implement observability, monitoring, governance, and production support mechanisms for AI systems.


• Drive model lifecycle management including versioning, experimentation tracking, and CI/CD automation.


• Mentor engineering teams and establish AI/ML engineering best practices.


• Collaborate with business stakeholders to identify and implement AI-driven solutions.


• Optimize AI systems for scalability, latency, reliability, and cost efficiency.

Required Skills & Qualifications

• Strong hands-on experience in Artificial Intelligence, Machine Learning, and Generative AI systems.


• Extensive experience in end-to-end ML lifecycle including data ingestion, feature engineering, model development, validation, deployment, monitoring, and retraining.


• Hands-on expertise with Python, SQL, APIs, and ML frameworks such as Scikit-learn, TensorFlow, PyTorch, Hugging Face, and LangChain.


• Experience with Vector Databases, RAG pipelines, semantic search, embeddings, and LLM orchestration.


• Strong expertise in MLOps tools including MLflow, DVC, Docker, Kubernetes, CI/CD pipelines, and model versioning.


• Hands-on experience with observability, logging, tracing, monitoring, drift detection, and model performance tracking.


• Experience building scalable cloud-native inference and AI deployment pipelines.


• Strong understanding of distributed systems, data engineering, and scalable AI infrastructure.


• Excellent stakeholder management and cross-functional collaboration skills.


• Experience with Azure Cloud Stack is a plus.