Vaishnavi R B
Sr. AI Engineer
Bangalore, IN.About
Google Cloud Certified Machine Learning Engineer with over 5 years of experience specializing in Generative AI, leading end-to-end development and deployment of scalable AI solutions. Proficient in language models, conversational AI, and agentic frameworks, I leverage advanced analytics and MLOps to drive product innovation and optimize system efficiency. Proven collaborator in deploying production-ready applications at scale, ensuring robust model performance and impactful business outcomes.
Work
Bangalore, Karnataka, India
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Summary
Led the end-to-end development and deployment of advanced Machine Learning and Generative AI solutions, optimizing model performance and integrating AI into enterprise workflows.
Highlights
Pioneered the research, development, and fine-tuning of advanced ML and Generative AI models, including LLMs (Gemini, GPTs), enhancing model behavior and contextual accuracy through prompt engineering and RAG techniques.
Engineered and integrated LLM-powered agents and multi-agent systems into enterprise workflows via RESTful APIs and WebSocket interfaces, facilitating task delegation, contextual search, and decision-making.
Designed and implemented robust ETL pipelines for collecting, preprocessing, and structuring large datasets (text, images, audio), ensuring high data quality, consistency, and bias mitigation for model training.
Deployed scalable ML/Gen AI models to AWS and GCP, optimizing inference speed and reducing computational costs through quantization and distillation techniques, while implementing real-time and batch processing.
Monitored model drift, hallucinations, and toxicity using custom evaluation metrics and MLOps tools like Kubeflow, establishing automated retraining pipelines and feedback loops for continuous improvement and alignment.
Developed RESTful APIs and integrated AI models with enterprise applications and chatbots, leveraging vector databases (Pinecone, FAISS, ChromaDB) for efficient retrieval-based AI solutions.
Bangalore, Karnataka, India
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Summary
Conducted comprehensive evaluations for anomaly detection models using cloud-based services, enhancing model performance and accuracy.
Highlights
Evaluated anomaly detection models using AWS Lookout and Azure Application Insights, identifying key performance indicators and improving detection accuracy.
Leveraged cloud-based anomaly detection services to assess model performance and accuracy, validating deployed models' effectiveness in detecting anomalies within ELK stack.
Analyzed detection results and fine-tuned models for improved anomaly identification and response accuracy, contributing to enhanced system reliability and operational efficiency.
Bangalore, Karnataka, India
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Summary
Gained foundational knowledge in cloud solution environments and full-stack development, contributing to an e-commerce website project.
Highlights
Achieved Associate Cloud Engineer certification, mastering the setup, planning, configuration, deployment, and successful operation of cloud solutions.
Developed practical knowledge in Java full-stack development, building an e-commerce website with Spring Boot for program logic and MySQL for backend database management.
Configured access and security protocols for cloud solutions, ensuring robust data protection and compliance.
Education
Skills
Cloud Platforms
Google Cloud Platform (GCP), AWS, Kubeflow, Cloud Run, BigQuery, Bigtable, MQTT Brokers, DocAI.
Generative AI & Machine Learning
Generative AI, Large Language Models (LLMs), Conversational AI, Document Intelligence, Agentic Frameworks (ADK, CrewAI, LangGraph), Machine Learning, Artificial Intelligence, Vertex AI, AutoML, Prompt Engineering, Few-shot Learning, Instruction Tuning, Retrieval-Augmented Generation (RAG), Model Drift Monitoring, Hallucination Mitigation, Model Optimization (Quantization, Pruning, Distillation).
Programming & Frameworks
Python, PyTorch, TensorFlow, Java, Spring Boot, FastAPI, HTML, CSS, JavaScript, Bootstrap, RESTful APIs, WebSocket.
Databases & Data Engineering
MySQL, Vector Databases (Pinecone, FAISS, ChromaDB), ETL Pipelines, Dataflow, BigQuery, Bigtable, Redis, Elasticsearch, Logstash, Kibana.
MLOps & Deployment
MLOps, Kubeflow, Production Deployment, Model Monitoring, Automated Retraining Pipelines, Real-time Processing, Batch Processing.
Analytical & Strategic
Advanced Analytics, Statistical Models, Optimization Frameworks, User Behavior Analysis, Product Innovation, Problem-Solving, Cross-functional Collaboration, Technical Leadership, Requirements Clarification.