About the Company: We are looking for a skilled AI/ML professional to develop, implement, and optimize machine learning models and AI solutions. The role involves data analysis, model training, and integrating AI into real-world applications to solve complex business problems efficiently.
About the Role: The role involves data analysis, model training, and integrating AI into real-world applications to solve complex business problems efficiently.
Responsibilities:
- Architect and implement advanced AI solutions leveraging LLMs (and other emerging architectures), embeddings, and agentic frameworks (e.g., OpenAI Agent SDK, AutoGPT, LangChain, Crew AI).
- Develop and refine Agentic AI systems focusing on planning, memory, tool utilization, and dynamic task critic execution.
- Engineer and optimize prompt engineering pipelines to achieve superior accuracy 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 deliver production-grade solutions that create tangible value. Stay ahead of the curve by integrating emerging Gene AI research and state-of-the-art capabilities into practical, real-world systems.
- Lead projects and mentor junior engineers, contributing to a culture of innovation and growth.
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).
- Core Knowledge: Deep understanding of Large Language Models (LLMs), embeddings, Retrieval Augmented Generation (RAG), and vector databases (e.g., FAISS, We aviate).
- 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.
