Machine Learning Engineer / Generative AI & Agentic Systems

Iquest Management Consultants; Pune District; On-site; INR 1,500,000 - 2,500,000; Full time

Job summary

Iquest Management Consultants is seeking a Machine Learning Engineer / Generative AI & Agentic Systems expert to design, deploy, and operate AI solutions for automotive applications in Pune. The role requires strong Python skills and production-oriented software experience, with familiarity in LLMs, vector databases, and enterprise AI tooling.

You will collaborate in Agile teams, build agentic AI systems with tool and API integrations, and ensure secure data handling while delivering business

Qualifications

• Masters or Bachelors degree in Computer Science, AI, ML, Data Science, Robotics, Engineering, Mathematics, or a related field.
• Professional experience of 2 to 3 years in machine learning engineering, data science, AI engineering, generative AI engineering, or a related technical role.
• Proven experience developing and deploying ML or DL models for real-world applications, especially in Automotive industries
• Strong Python programming skills, including production-oriented software; knowledge of C++ or .NET is a plus.
• Strong knowledge of ML architectures, techniques, and evaluation methods, esp. CV, DL, anomaly detection, forecasting, optimisation, and generative AI.
• Experience with LLMs, embedding models, transformers, prompt engineering, fine-tuning, inference optimisation, and model evaluation.
• Hands-on experience with Azure OpenAI Service or equivalent LLM platforms for enterprise-grade generative AI apps.
• Experience building RAG systems with document ingestion, embedding, vector search, semantic search, reranking, grounding, and citation generation.
• Experience with Azure AI Search, vector databases, semantic search platforms, or enterprise search systems.
• Experience designing agentic AI systems including tool calling, API integration, workflow orchestration, planning, multi-agent collaboration, structured outputs, memory, guardrails, and human approval mechanisms.
• Experience or familiarity with Model Context Protocol, MCP server development, MCP tool integration, secure data access, and connecting agents to enterprise systems.
• Familiarity with agentic AI frameworks such as Azure AI Foundry Agent Service, Microsoft Agent Framework, Semantic Kernel, LangChain, LangGraph, AutoGen, CrewAI.
• Ability to design AI agents that interact with databases, APIs, documents, business systems, and internal tools securely.
• Ability to analyse complex data, identify practical opportunities, and translate technical findings into actionable business recommendations.
• Strong communication skills to explain technical concepts to technical and non-technical stakeholders.
• Ability to work effectively in cross-functional and Agile environments.
• Self-motivated, pragmatic, and comfortable in fast-moving technical environments.

Responsibilities

• Develop and deploy machine learning or deep learning models for real-world automotive applications.
• Build enterprise-grade generative AI applications using Azure OpenAI and related platforms.
• Design agentic AI systems with tool calling, API integration, and workflow orchestration.
• Evaluate models, monitor performance, and ensure secure data access for enterprise use.
• Collaborate with cross-functional teams in Agile sprints to translate findings into business impact.
• Document and present technical concepts to both technical and non-technical stakeholders.

Skills

Python

LLMs

Communication

Cross-functional teamwork

Agile methodologies

Education

Bachelor's or Master’s in CS/AI/ML

Tools

Azure OpenAI Service

LangChain

Semantic Kernel

Vector databases

APIs integration

Job description

Role & responsibilities

Job description:

I) Machine Learning Engineer / Generative AI & Agentic Systems

• Masters or Bachelors degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Robotics, Engineering, Mathematics, or a related field.
• Professional experience of 2 to 3 years in machine learning engineering, data science, AI engineering, generative AI engineering, or a related technical role.
• Proven experience developing and deploying machine learning or deep learning models for real-world applications, especially in Automotive industries
• Strong Python programming skills, including experience building maintainable, tested, production-oriented software. Knowledge of other programming languages, notably C++ or .NET, is a significant plus.
• Strong knowledge of machine learning architectures, techniques, and evaluation methods, particularly in computer vision, deep learning, anomaly detection, forecasting, optimisation, and generative AI.
• Experience with LLM, embedding models, transformer architectures, prompt engineering, fine-tuning, inference optimisation, and model evaluation.
• Hands-on experience with Azure OpenAI Service or equivalent LLM platforms for building enterprise-grade generative AI applications.
• Experience building RAG systems, including document ingestion, chunking, embedding generation, vector search, semantic search, reranking, grounding, citation generation, and retrieval evaluation.
• Experience with Azure AI Search, vector databases, semantic search platforms, or enterprise search systems.
• Experience designing or implementing agentic AI systems, including tool calling, API integration, workflow orchestration, planning, multi-agent collaboration, structured outputs, memory, guardrails, and human approval mechanisms.
• Experience or strong familiarity with Model Context Protocol, including MCP server development, MCP tool integration, secure data access, and connecting agents to enterprise systems.
• Familiarity with agentic AI frameworks such as Azure AI Foundry Agent Service, Microsoft Agent Framework, Semantic Kernel, LangChain, LangGraph, AutoGen, CrewAI, or equivalent orchestration frameworks.
• Ability to design AI agents that interact with databases, APIs, documents, business systems, and internal tools using secure and auditable integration patterns.
• Ability to analyse complex data, identify practical opportunities, and translate technical findings into actionable business recommendations.
• Strong communication skills, with the ability to explain technical concepts clearly to technical and non-technical stakeholders.
• Ability to work effectively in cross-functional and Agile environments.
• Self-motivated, pragmatic, and comfortable operating in fast-moving technical environments.