Software Engineer- AI/ML

Role Overview: You are an experienced AI Engineer with 4-5 years of hands-on experience in designing and implementing AI solutions. Your role involves developing AI/ML-based solutions, specializing in Computer Vision (OpenCV) and deploying Large Language Models (LLMs) like GPT, LLaMA, or custom fine-tuned models. You will work on cutting-edge AI applications, collaborating with Product, Data Science, and Engineering teams to optimize AI/ML models for real-world business applications. Key Responsibilities: - Research, design, and develop AI/ML solutions for real-world business applications, ensuring RAG implementation. - Collaborate with Product & Data Science teams to define core AI/ML platform features. - Analyze business requirements and select pre-trained models that align with specific use cases. - Utilize multi-agent AI frameworks like LangChain, LangGraph, and LlamaIndex. - Train and fine-tune LLMs (GPT, LLaMA, Gemini, etc.) for domain-specific tasks. - Implement Retrieval-Augmented Generation (RAG) workflows and optimize LLM inference. - Develop NLP-based GenAI applications such as chatbots, document automation, and AI agents. - Preprocess, clean, and analyze large datasets to enhance AI models. - Optimize LLM inference speed, memory efficiency, and resource utilization. - Deploy AI models in cloud environments (AWS, Azure, GCP) or on-premises infrastructure. - Create APIs, pipelines, and frameworks for integrating AI solutions into products. - Conduct performance evaluations and fine-tune models for accuracy, latency, and scalability. - Stay updated with advancements in AI, ML, and GenAI technologies. Qualifications Required: - Strong experience in developing & deploying AI/ML models. - Expertise in LLM pretraining, fine-tuning, and optimization. - Hands-on experience in NLP, Transformers, OpenCV, YOLO, R-CNN. - Experience with LangChain, LangGraph, LlamaIndex. - Proficiency in TensorFlow, PyTorch, Keras. - Strong knowledge of AWS, Azure, or GCP for AI deployment. - Experience in LLM inference optimization for speed & memory efficiency. - Proficiency in Python and experience in API development. - Knowledge of Regression, Classification, Clustering, SVMs, Decision Trees, Neural Networks. - Strong skills in unit testing, debugging, and model evaluation. - Hands-on experience with Vector Databases (FAISS, ChromaDB, Weaviate, Pinecone).,