Description

You will design and implement autonomous AI agents and machine learning systems for structured and unstructured data.

This role is hybrid.

Responsibilities

• Build systems with planning, memory, tool usage, and multi-step reasoning using LLMs.
• Develop multi-agent architectures for collaborative task execution and feedback loops.
• Train, tune, and deploy ML/DL models, ensuring performance through rigorous validation.
• Implement RAG pipelines, advanced prompt chaining, and LLM adaptation via LoRA or PEFT.
• Apply NLP, computer vision, or time-series techniques to solve complex data problems.

Required Skills

• 5+ years of experience in Data Science and Machine Learning.
• Hands-on expertise with LLMs, including GPT-based and open-source models.
• Proficiency in RAG (Retrieval-Augmented Generation) and prompt engineering.
• Experience with model fine-tuning techniques such as LoRA, PEFT, or instruction tuning.
• Strong background in feature engineering, model selection, and hyperparameter tuning.
• Ability to design and implement autonomous agent workflows.

Key Skills

Education

Any Gradute