AI ML Developer
About the position
Wipro is seeking a talented AI/ML Developer to join their team, focusing on developing, deploying, and fine-tuning machine learning models using Google Cloud Platform tools like Vertex AI. This role involves working with advanced Large Language Models (LLMs) and building RAG (Retrieval-Augmented Generation) pipelines, while collaborating with cross-functional teams to create scalable AI solutions that meet business needs.
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 various 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.
Requirements
• 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.
Nice-to-haves
• 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.
Benefits
• Competitive pay
• Day one benefits
• Opportunities for career advancement
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