Senior AI ML Developer
DIAN Technology Solutions Pvt Ltd
Location
🇮🇳 India
Type
full_time
Salary
Undisclosed
Posted
4d ago
Job Description
Position Type: Full-Time, Permanent (FTE) Experience: 5 – 8 Years Location: Chennai, India Work Mode: Work from Office Joining: Immediate Joiner Preferred POSITION
OVERVIEW
We are seeking a highly skilled and forward-thinking Senior AI & Machine Learning Engineer for our client to join there core engineering unit in Chennai. In this permanent, full-time role, you will lead the architecture, design, and deployment of production-grade AI applications, with a heavy emphasis on Large Language Models (LLMs) and advanced Agentic AI frameworks. The ideal candidate possesses deep technical expertise in traditional machine learning pipelines along with extensive practical experience building autonomous, multi-agent workflows capable of complex planning, reasoning, and tool utilization. As a permanent office-based team member, you will collaborate closely with cross-functional software architects and product owners to integrate intelligence directly into enterprise systems.
KEY RESPONSIBILITIES
Agentic System Architecture: Design, build, and optimize robust autonomous AI agents and multi-agent systems utilizing frameworks like LangGraph, AutoGen, or CrewAI to execute sophisticated workflows. LLM Customization & Engineering: Select, fine-tune, prompt-engineer, and deploy state-of-the-art open-source and proprietary Large Language Models (LLMs) specialized for complex reasoning and workflow tasks. ML Pipeline Development: Build, scale, and maintain end-to-end Machine Learning pipelines, including data pre-processing, feature engineering, model training, validation, and real-time inference serving. Retrieval-Augmented Generation (RAG): Architect and fine-tune scalable RAG architectures integrated with vector databases to provide contextually accurate knowledge injection for production agents. Performance Optimization: Monitor, evaluate, and optimize the execution latency, cost, and accuracy of AI agents and foundational models in production environments. On-Site Collaboration: Drive cross-functional engineering excellence within the office workspace, mentoring junior developers and establishing technical best practices for reproducible AI codebases.