JOB ID:QT-SNB-08-349

Role Overview

We are looking for an experienced ML Engineer - Generative AI & Agentic AI with strong expertise in Python, Machine Learning, Generative AI, Agentic AI, and Microsoft Azure.

The ideal candidate will have hands-on experience building and deploying machine learning models, developing scalable ML pipelines, creating AI agents, and orchestrating intelligent agentic workflows using Azure Data and AI platforms.

You will work closely with engineering, data, and AI teams to design and deliver secure, scalable, production-grade AI solutions.

Key Responsibilities

- Design, develop, and maintain scalable machine learning pipelines and integrate them with Azure ML.
- Develop and deploy machine learning models using Python, TensorFlow, PyTorch, or equivalent frameworks.
- Design and implement Generative AI and LLM-based solutions for enterprise applications.
- Build intelligent AI agents capable of planning, reasoning, tool usage, and decision-making.
- Design and implement agentic AI workflows and orchestration frameworks.
- Build secure, scalable, and production-ready architectures for AI agents and LLM applications.
- Work extensively with Microsoft Azure, including Azure ML, Azure Databricks, Microsoft Fabric, and Microsoft AI Foundry.
- Develop RAG pipelines, prompt engineering solutions, and LLM-powered applications.
- Implement AI agent safety, guardrails, evaluation, observability, and monitoring mechanisms.
- Develop feedback loops to continuously improve agent performance and reliability.
- Analyze user interactions and system feedback to improve AI agent behavior and decision-making.
- Support model serving, deployment, monitoring, optimization, and productionization of AI systems.
- Collaborate with backend,



data engineering, ML platform, and frontend teams to deliver end-to-end AI solutions.
- Conduct experiments and performance evaluations for models, agents, prompts, and AI workflows.
- Rapidly prototype, test, and iterate on AI solutions in a fast-paced environment.
- Collaborate with senior engineers, architects, and researchers to deliver production-grade AI systems.

Required Qualifications
- 6-8 years of experience in Machine Learning / AI Engineering.
- Strong hands-on programming experience with Python.
- Strong experience with TensorFlow, PyTorch, or equivalent machine learning frameworks.
- Proven experience building and deploying machine learning models in production.
- Hands-on experience developing Generative AI, LLM, and Agentic AI solutions.
- Solid knowledge of Microsoft Azure AI and Data platforms.
- Hands-on experience with:
- Azure ML
- Azure Databricks
- Microsoft Fabric
- Microsoft AI Foundry

- Experience designing and implementing ML pipelines and deployment architectures.
- Strong understanding of AI agent orchestration, tool calling, planning, reasoning, evaluation, and monitoring.
- Experience with production AI systems, model serving, scalability, and performance optimization.
- Solid problem-solving and analytical skills.
- Ability to work effectively in a fast-paced and collaborative environment.

Good to Have




- Experience with Reinforcement Learning and agent feedback mechanisms.
- Knowledge of RAG architectures, vector databases, embeddings, and semantic search.
- Strong understanding of Prompt Engineering and LLM optimization.
- Experience with LLM evaluation frameworks and evaluation metrics.
- Knowledge of AI safety, responsible AI, guardrails, and content filtering.
- Experience with model fine-tuning, PEFT/LoRA, or other LLM optimization techniques.
- Experience integrating AI systems with REST APIs, backend services, and frontend applications.
- Experience building AI solutions for enterprise or security-focused applications.
- Knowledge of CI/CD, MLOps, containerization, and cloud-native deployment practices.

Key Skills Must Have

Python | Machine Learning | Azure ML | Generative AI | LLM | Agentic AI | TensorFlow/PyTorch | Azure Databricks | Microsoft Fabric | Microsoft AI Foundry | ML Pipelines | AI Agent Deployment

Good to Have

Reinforcement Learning | RAG | Prompt Engineering | AI Safety & Guardrails | LLM Evaluation | Vector Databases | Model Fine-Tuning | MLOps | APIs

What We re Looking For

We are looking for someone who can go beyond experimentation and build production-ready AI systems. The candidate should be comfortable working across ML engineering, Generative AI, agentic workflows, Azure platforms, deployment, evaluation, and monitoring, with a strong focus on scalability, security, and reliability.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 ML Engineer - Generative AI & Agentic AI (Nagpur)
🏢 Qloron Technology
📍 Nagpur