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ML/GenAI Engineer

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Hybrid

ML/GenAI Engineer

Nisum

ML/GenAI Engineer

Skills

Data EngineeringDockerPythonDatabricksGitMachine LearningAIKubernetesComplianceAzure

2 months ago

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Important information


Contract type:

Permanent

Salary:

₹1,000,000 – ₹2,000,000 / year

Location:

Bhubaneswar, Odisha, India

Work mode:

Hybrid

Published on:

7 August 2026

What they need


Machine Learning Engineer / Generative AI Engineer

Experience: - 5-15 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

  • 510 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.Role & responsibilities

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