Job Description

- The job role is for an AI/ML Engineer specializing in machine learning and NLP.
- The employee will be responsible for deploying and managing AI models on the Google Cloud Platform (GCP) and On-Prem.
- The role requires hands-on experience working on Large Language Models (LLMs) and/or developing Conversational AI Systems.
- Key responsibilities include the design, development, and deployment of conversational AI systems such as chatbots and virtual assistants.
- The candidate will develop multi modal solution architecture with bespoke models for specific use-cases and scenarios.
- They are expected to fine-tune and optimize LLM models for specific banking tasks and user experiences.
- Implementing Retrieval Augmented Generation (RAG) and embeddings to retrieve customer information through APIs is another key responsibility.
- The role involves continuous monitoring and evaluation of the performance of voice-based banking solutions.
- The candidate will develop and deploy machine learning models for tasks like personalized recommendations and customer sentiment analysis.
- They will collaborate to deploy and manage models on GCP, leveraging MLOps tools and services to streamline model development, training, and deployment.
- The employee will develop an end-to-end architecture from training to inferencing custom models.
- The job requires a strong understanding of natural language processing (NLP) concepts and techniques, good programming skills, and knowledge of AI/ML algorithms for building NLP Applications.
- Deep knowledge of LLM architectures and their applications, expertise in data preprocessing, feature engineering, and model evaluation is needed.
- A basic understanding of MLOps principles and practices is required along with excellent problem-solving and communication skills.
- The candidate should have 3+ years of hands-on experience in AI/ML development, with a strong focus on NLP & API Integrations.
- Experience with LLM models, fine-tuning, prompt engineering, and RAG techniques is required.
- Proficiency in Python is a must, and knowledge of vector databases will be beneficial.
- Hands-on experience with frameworks like TensorFlow, Pytorch, LangChain, FastAPIs, NoSQL Database is required.
- Knowledge of GCP/MLOPs will be a plus.

Skills Required