AI ML Developer - Wipro Ltd

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