AI/ML Engineer

Role Overview

We are looking for a highly skilled ML/AI Engineer to join our team on a full time basis. The ideal candidate will have strong hands-on experience in Python, SQL, Machine Learning, and Large Language Models (LLMs). You will work on innovative AI/GenAI solutions involving RAG, prompt engineering, LLM integration, and data pipelines, while solving real-world business problems and delivering scalable solutions.

Responsibilities

• Develop, test, optimize, and deploy ML and LLM-based solutions using Python, SQL, and relevant frameworks.
• Build practical GenAI use cases, including prompt engineering, RAG, and LLM-powered applications.
• Integrate LLM solutions with data pipelines, databases, APIs, and downstream applications.
• Translate business requirements into effective and deployable AI/ML solutions.
• Monitor, debug, evaluate, and continuously improve LLM applications and workflows.
• Work closely with cross-functional teams to deliver high-quality solutions within timelines.
• Research and experiment with emerging GenAI and LLM technologies to identify opportunities for innovation.
• Ensure solutions are reliable, scalable, maintainable, and aligned with business objectives.

Requirements

• 2+ years of relevant professional experience in ML, AI, Data Science, or GenAI.
• Strong hands-on experience with Python and SQL.
• Experience developing and deploying ML/LLM-based solutions in practical or production environments.
• Hands-on experience with LLM frameworks such as LangChain or similar tools.
• Strong experience with RAG, prompt engineering, and LLM integration.
• Experience integrating AI/LLM solutions with data pipelines and applications.
• Strong analytical, problem-solving, and debugging skills.
• Ability to translate complex business requirements into practical technical solutions.
• Excellent communication skills.
• Ability to work independently as well as effectively within a fast-paced, cross-functional environment.

Skills

• Python
• SQL
• LangChain
• RAG
• Large Language Models

Nice to Have

• Experience with LLM fine-tuning or reinforcement learning (RL).
• Exposure to AI agents and agentic workflows.
• Experience debugging and monitoring multi-step or long-running LLM applications.
• Experience working with modern ML/AI frameworks, cloud platforms, or MLOps tools.

Benefits

• Flexible schedule
• Paid sick time
• Provident Fund