Machine Learning & Generative AI Engineer

Nisum; Khordha, Hyderabad; On-site; INR 1,200,000 - 2,400,000; Full time

Job summary

Nisum, a leading technology consulting company, is seeking an experienced Machine Learning Engineer / Generative AI Engineer to design, deploy, and operate enterprise-scale AI solutions in cloud environments.

You will work with cross-functional teams to build intelligent applications, implement AI workflows, and establish scalable AI platforms that deliver measurable business value. This role emphasizes MLOps, security, and cost optimization in production.

Qualifications

• 5–10 years of experience in Machine Learning Engineering, AI Platform Engineering, MLOps, or related domains.
• Strong proficiency in Python and experience building production-grade AI/ML applications and services.
• Hands-on experience with Generative AI and Large Language Model (LLM) applications in enterprise environments.
• Expertise in Retrieval-Augmented Generation (RAG), vector search, embeddings, and retrieval pipelines.

Responsibilities

• Deploy, scale, and manage Machine Learning and Generative AI solutions in cloud environments, with a preference for Azure-based ecosystems.
• Design and develop enterprise-grade Retrieval-Augmented Generation (RAG) applications using embeddings, vector databases, and retrieval pipelines.
• Build and operationalize Agentic AI workflows with tool integration using LangChain and LangGraph.
• Develop reusable AI infrastructure and orchestration frameworks using MCP and ADK.
• Design and implement model-serving architectures, including REST APIs, batch inference, and real-time AI services.
• Establish best practices for observability, monitoring, evaluation, governance, and performance optimization of AI systems.
• Collaborate with Data Engineering, Application Development, and Business teams to integrate AI solutions into enterprise workflows.
• Drive adoption of MLOps and LLMOps practices, including CI/CD automation, model versioning, testing, deployment, and lifecycle management.
• Ensure security, compliance, reliability, scalability, and cost optimization of AI services deployed in production environments.
• Contribute to architectural decisions and continuously improve AI platform capabilities.

Skills

Python

Generative AI

LLM Applications

MLOps

Azure Cloud

Kubernetes

LangChain/LangGraph

Retrieval-Augmented Generation

Vector Databases

REST APIs

Education

Bachelor’s Degree in Computer Science or related field

Tools

Docker

Kubernetes

Azure ML

Databricks

LangChain

LangGraph

LangSmith

REST APIs

Job description

Machine Learning Engineer / Generative AI Engineer

Experience:510 Years
Location:Hyderabad / / Bhubaneswar
Employment Type:Full-Time

About the Role

We are seeking an experienced Machine Learning Engineer / Generative AI Engineer to join our growing AI team. In this role, you will be responsible for designing, deploying, and operating enterprise-scale AI and Generative AI solutions in cloud-based production environments. You will work closely with cross-functional teams to build intelligent applications, implement AI workflows, and establish scalable AI platforms that deliver measurable business value.

Key Responsibilities

• Deploy, scale, and manage Machine Learning and Generative AI solutions in cloud environments, with a preference for Azure-based ecosystems.
• Design and develop enterprise-grade Retrieval-Augmented Generation (RAG) applications using embeddings, vector databases, and retrieval pipelines.
• Build and operationalize Agentic AI workflows with tool integration using frameworks such as LangChain and LangGraph.
• Develop reusable AI infrastructure and orchestration frameworks using Model Context Protocol (MCP) and AI Development Kit (ADK).
• Design and implement model-serving architectures, including REST APIs, batch inference, and real-time AI services.
• Establish best practices for observability, monitoring, evaluation, governance, and performance optimization of AI systems.
• Collaborate with Data Engineering, Application Development, and Business teams to integrate AI solutions into enterprise workflows.
• Drive adoption of MLOps and LLMOps practices, including CI/CD automation, model versioning, testing, deployment, and lifecycle management.
• Ensure security, compliance, reliability, scalability, and cost optimization of AI services deployed in production environments.
• Contribute to architectural decisions and continuously improve AI platform capabilities.

Required Skills & Experience

• 5–10 years of experience in Machine Learning Engineering, AI Platform Engineering, MLOps, or related domains.
• Strong proficiency in Python and experience building production-grade AI/ML applications and services.
• Hands-on experience with Generative AI and Large Language Model (LLM) applications in enterprise environments.
• Expertise in Retrieval-Augmented Generation (RAG), vector search, embeddings, and retrieval pipelines.
• Experience with orchestration frameworks such as LangChain, LangGraph, and LangSmith.
• Strong understanding of AI model serving, inference pipelines, monitoring, and observability.
• Experience with Azure AI, Azure Machine Learning, Databricks, or similar cloud AI platforms.
• Hands-on experience with Docker, Kubernetes, REST APIs, and cloud-native deployments.
• Knowledge of MLOps/LLMOps practices, including CI/CD, testing, version control, and deployment automation.
• Strong problem-solving skills and the ability to work in a collaborative, fast-paced environment.

Educational Qualification

• Bachelor’s Degree in Computer Science, Information Systems, Engineering, Computer Applications, or a related field.