# Madhu Ramakrishnappa

> AI/ML Engineer | LLMs, RAG, GenAI | PyTorch, TensorFlow | AWS, GCP, Azure | MLOps, Kubernetes | NLP & Time-Series

Location: San Jose, California, United States
Profile: https://flows.cv/madhuramakrishnappa

AI/ML Engineer with 4+ years of experience building scalable machine learning and generative AI systems across enterprise environments. I specialize in developing end-to-end solutions using deep learning, NLP, and large language models, with a strong focus on production deployment and measurable business impact.

At Northern Trust, I developed transformer-based recommendation systems that improved accuracy by 14% and increased customer engagement by 12%. I also engineered RAG pipelines using LangChain and Pinecone, improving enterprise knowledge retrieval accuracy by 19%. My work includes time-series forecasting models that reduced stock-outs by 18% and real-time data pipelines that decreased reporting latency by 42%.

Previously at TCS, I built churn prediction systems that reduced customer attrition by 12% and optimized ML workflows on AWS, improving latency by 31%. I have hands-on experience with LLM fine-tuning (LoRA, QLoRA), vector databases, and multi-agent systems, along with strong MLOps practices using Kubernetes, MLflow, and CI/CD pipelines.

I am passionate about building reliable, scalable AI systems that bridge research and production.
Skills: Python, SQL, PyTorch, TensorFlow, LangChain, LLMs (GPT-4, LLaMA, Mistral), RAG, Kubernetes, AWS, GCP, Azure ML, MLflow

## Work Experience
### AI/ML Engineer @ Northern Trust
Jan 2024 – Present | United States
• Developed Transformer-based recommendation models using PyTorch/TensorFlow and applied model distillation to optimize inference performance, improving recommendation accuracy by 14% while increasing customer engagement by 12%.
• Engineered LangChain RAG pipelines with Pinecone vector databases and implemented LLM evaluation frameworks, enhancing query relevance by 19% and improving enterprise knowledge retrieval accuracy across internal systems.
• Designed time-series forecasting models in TensorFlow/Prophet, reducing stock-out frequency by 18%, improving warehousedistribution accuracy, and optimizing retail demand planning workflows.
• Implemented real-time Kafka pipelines orchestrated with Airflow, decreasing reporting latency by 42%, enabling timely analytics delivery for supply chain monitoring systems.
• Introduced A/B testing frameworks for ML validation, improving performance reliability by 11% while ensuring statistically valid deployment of production-ready machine learning models.
• Deployed monitoring with MLflow + Prometheus, enabling drift detection, tracking latency metrics, and ensuring SLA compliance across enterprise-level machine learning deployments.

### AI/ML Engineer @ Tata Consultancy Services
Jan 2021 – Jan 2023
• Built churn prediction frameworksin PyTorch/TensorFlow,reducing attrition by 12% acrosstelecom and retail portfolios, improving longterm customer retention strategies.
•  Migrated machine learning workflows to Amazon Web Services (AWS), lowering latency by 31%, achieving scalability improvements and sustaining production-ready throughput for critical ML applications.
• Configured Spark/Hadoop clustersfor distributed training, reducing dataset preprocessing time from six hoursto two, accelerating largescale training efficiency significantly.
• Applied Hugging Face Transformers to unstructured review data, improving sentiment classification accuracy 16% compared to baseline systems, ensuring reliable text classification at production scale.
• Automated deployment pipelines with Kubernetes, reducing failed releases 40%, improving reproducibility, and stabilizing production ML workflows across multi-tenant enterprise environments.
• Built anomaly detection monitoring with Grafana + ELK Stack, ensuring SLA adherence and supporting predictive maintenance for multitenant enterprise production ML pipelines.


## Education
### Master of Science - MS in Information Technology
UMass Boston

### Bachelor of Engineering - BE in Computer Science
Visvesvaraya Technological University


## Contact & Social
- LinkedIn: https://linkedin.com/in/mrk16

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Source: https://flows.cv/madhuramakrishnappa
JSON Resume: https://flows.cv/madhuramakrishnappa/resume.json
Last updated: 2026-04-17