Job
Description
Role & responsibilities Design, build, and optimize machine/deep learning models, including predictive models, recommendation systems, and Gen-AI-based solutions. Develop and implement advanced AI agents capable of performing autonomous tasks, decision-making, and executing requirement-specific workflows. Prompt engineer to develop new and enhance existing Gen-AI applications. (Chatbots, RAG) Perform advanced data manipulation, cleansing, and analysis to extract actionable insights from structured and unstructured data. Create scalable and efficient recommendation systems that enhance user personalization and engagement. Design and deploy AI-driven chatbots and virtual assistants, focusing on natural language understanding and contextual relevance. Implement and optimize machine and deep learning models for NLP tasks, including text classification, sentiment analysis, and language generation. Explore, develop, and deploy state-of-the-art technologies for AI agents, integrating them with broader enterprise systems. Collaborate with cross-functional teams to gather business requirements and deliver AI-driven solutions tailored to specific use cases. Automate workflows using advanced AI tools and frameworks to increase efficiency and reduce manual interventions. Stay informed about cutting-edge advancements in AI, machine learning, NLP, and GenAI applications, and assess their relevance to the organization. Effectively communicate technical solutions and findings to both technical and non-technical stakeholders. Required: At least 3 years of experience working with data sciences. Python proficiency and hands-on experience with libraries like (Pandas, Numpy, Matplotlib, NLTK, Sklearn, and Tensorflow) Proven experience in designing and implementing AI agents and autonomous systems. Strong expertise in machine learning, including predictive modeling and recommendation systems. Hands-on experience with deep learning frameworks like TensorFlow or PyTorch, focusing on NLP and AI-driven solutions. Advanced understanding of natural language processing (NLP) techniques and tools, including transformers like BERT, GPT, or similar models including open-source LLMs. Experience in prompt engineering for AI models to enhance functionality and adaptability. Strong knowledge of cloud platforms (AWS) for deploying and scaling AI models. Familiarity with AI agent frameworks like LangChain, OpenAI APIs, or other agent-building tools. Advanced skills in Relational databases [Postgres], Vector Database, querying, analytics, semantic search, and data manipulation. Strong problem-solving and critical-thinking skills, with the ability to handle complex technical challenges. Hands-on experience working with API frameworks like Flask, FastAPI, etc. Git and GitHub proficiency. Excellent communication & documentation skills to articulate complex ideas to diverse audiences. Preferred: Hands-on experience building and deploying conversational AI, chatbots, and virtual assistants. Familiarity with MLOps pipelines and CI/CD for AI/ML workflows. Experience with reinforcement learning or multi-agent systems. BE (OR Master) in Computer Science, Data Science, or Artificial Intelligence. Agentic AI systems using frameworks like Langchain or similar.
