Ai Ml Engineer

Responsibilities:

Architect and implement advancedAI solutions leveraging LLMs (and otheremerging architectures), embeddings, and agentic frameworks (e.g., OpenAI Agent SDK, AutoGPT, LangChain, CrewAI).

Develop and refine AgenticAI systems focusingon planning, memory,tool utilization, and dynamic task critic execution.

Engineer and optimize prompt engineering pipelines to achieve superioraccuracy and low latency across diverse applications.

Fine-tune and deploy specialized LLMs and AI copilots to transform engineering and business operations.

Collaborate with cross-functional teams to deliverproduction-grade solutions that create tangible value.

Stay ahead of the curve by integrating emergingGenAI research and state-of-the-art capabilities into practical, real-world systems.

Lead projects and mentor juniorengineers, contributing to a cultureof innovation and growth

Required Qualifications:

Experience: 3-8 years of hands-on ML/AI/Deep Learning experience, with a strong portfolio of real world application development.

Technical Proficiency: Advanced Python skills and extensive experience with leading AI tools and libraries (OpenAI, Hugging Face, LangChain, PyTorch, TensorFlow). C

ore Knowledge: Deep understanding of Large Language Models (LLMs), embeddings, Retrieval Augmented Generation (RAG), and vector databases (e.g., FAISS, Weaviate).

Prompt Engineering Mastery: Proven expertise in designing and implementing effective, reusable prompts for complex reasoning, classification, generation, and tool integration tasks across a wide variety of models including open-source solutions.

Agentic AI Acumen: Prior experience with autonomous AI agents or multi-agent orchestration is a significant advantage.

Mindset: A startup-ready attitude - agile, intellectually curious, and hands-on, thriving in fast paced, iterative environments