Here we grow again with new opportunities! Wipro is seeking individuals who combine excellent customer service and problem-solving skills with the ability to function effectively both as part of a team or on an individual basis to bring their talent to our team. Wipro is a leading global IT Solutions and Services company with over 200,000 dedicated employees serving clients across more than 66 countries. We offer a strong compensation package that includes competitive pay and day one benefits. Wipro also offers many opportunities for career advancement within our engaging and exciting culture. 100% Remote USC and Green Card only No relocation Overview We are looking for a talented AI/ML Developer with experience in developing, deploying, and fine-tuning machine learning models using Google Cloud Platform (GCP) tools like Vertex AI. This role involves working with state-of-the-art Large Language Models (LLMs), building and maintaining RAG (Retrieval-Augmented Generation) pipelines, and handling complex data preprocessing tasks. The ideal candidate has a strong foundation in machine learning and AI technologies, along with hands-on experience with cloud-based AI/ML platforms such as Vertex AI and AWS Bedrock. You will collaborate with cross-functional teams to build scalable, high-performance AI solutions that meet business requirements. Key Responsibilities Develop, deploy, and fine-tune Large Language Models (LLMs) on platforms like Vertex AI and AWS Bedrock. Build, optimize, and maintain RAG (Retrieval-Augmented Generation) pipelines to support data-driven decision-making and enhance model accuracy. Perform complex data preprocessing, including cleaning, feature engineering, and transformation, to prepare data for ML pipelines. Design and implement scalable machine learning models for a variety of business applications, focusing on NLP and generative AI. Utilize Vertex AI, AWS Bedrock, or similar cloud-based tools to manage the entire ML lifecycle, from model training to deployment. Collaborate with data engineers, data scientists, and software engineers to integrate AI/ML models into production systems. Conduct model evaluation, A/B testing, and continuous improvement through hyperparameter tuning and retraining. Monitor and manage deployed models to ensure their performance, scalability, and reliability over time. Document technical processes, model architecture, and key decisions for ongoing maintenance and knowledge sharing. Qualifications Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, or a related field. 3+ years of experience in AI/ML development, with hands-on experience in model training, deployment, and monitoring. Proficiency with GCP tools such as Vertex AI and familiarity with similar platforms like AWS Bedrock for model deployment and management. Experience in developing, fine-tuning, and deploying Large Language Models (LLMs). Strong understanding of NLP, deep learning frameworks (such as TensorFlow or PyTorch), and generative AI techniques. Solid grasp of data preprocessing techniques for structured and unstructured data. Proficiency in programming languages such as Python and experience with ML libraries like scikit-learn, Hugging Face Transformers, and TensorFlow. Skills Experience with RAG pipelines, including building custom retrieval mechanisms and integrating with LLMs. Knowledge of model evaluation techniques and experience in A/B testing for model validation. Familiarity with cloud computing concepts and experience in deploying AI/ML models in a cloud environment. Hands-on experience with big data processing tools, such as Apache Beam, Dataflow, or BigQuery. Ability to work with APIs to integrate AI models with external data sources and systems. Strong problem-solving skills and the ability to work independently and as part of a team. Excellent communication skills, with the ability to collaborate effectively with technical and non-technical stakeholders. Preferred Qualifications Experience with MLOps practices, including model versioning, CI/CD for ML, and pipeline automation. Familiarity with Google Cloud Storage, BigQuery, and other GCP services. Knowledge of vector databases and experience working with semantic search Exposure to data labeling and active learning techniques for improving model performance. Experience in developing scalable AI/ML solutions for NLP tasks such as entity extraction, text summarization, and question answering