Description

Key Responsibilities

• Design, develop, and implement end-to-end AI/ML models and solutions for complex business problems.
• Work extensively with LLMs, Generative AI, and Retrieval-Augmented Generation (RAG) architectures.
• Build and optimize ML pipelines using frameworks such as TensorFlow, PyTorch, or Hugging Face Transformers.
• Leverage vector databases (e.g., FAISS, Pinecone, ChromaDB) for efficient similarity search and data retrieval.
• Integrate LangChain or LlamaIndex for developing intelligent, context-aware applications.
• Deploy, monitor, and maintain ML models on AWS, GCP, or Azure environments.
• Research and apply cutting-edge NLP, deep learning, and machine learning algorithms.
• Collaborate with cross-functional teams including data engineers, software developers, and product managers to deliver AI-driven solutions.
• Continuously evaluate and improve existing AI/ML models and workflows.

Required Skills

• Bachelor's degree in engineering or relevant field
• 7+ years of hands-on experience in Machine Learning and AI development.
• Strong proficiency in Python and familiarity with major ML frameworks (TensorFlow, PyTorch, Hugging Face).
• Proven experience with LLMs, Generative AI, and RAG-based solutions.
• Working knowledge of vector databases such as FAISS, Pinecone, or ChromaDB.
• Strong understanding of ML algorithms, deep learning architectures, and NLP techniques.
• Experience deploying models on cloud platforms (AWS, GCP, Azure).
• Familiarity with LangChain or LlamaIndex for LLM-based application development (preferred)
• Expertise in ETL/ELT Tools and Data Warehousing
• Strong Programming and Scripting Proficiency to build data pipelines
• Experience with Big Data Technologies like Apache Spark and Cloud Platforms services like S3, Data Factory, EMR, HDInsight, Dataflow
• Excellent problem-solving and analytical skills.
• Ability to work in a dynamic, fast-paced environment with minimal supervision

Key Skills

Education

Bachelor's degree