I am an AI Scientist and Machine Learning Engineer with 4 years of experience building intelligent systems using LLMs, transformer architectures, generative AI, multi-agent systems, and cloud-native ML workflows.
Experience
2024 — Now
2024 — Now
California, United States
Engineered a multi-agent AI system using JAX and TensorFlow to generate and validate biomedical hypotheses, integrating RAG pipelines over
40M+ genomic and chemical entries, reducing experimental search time from 48 to 31 hours per batch.
Designed and trained transformer-based models for protein interaction prediction and drug repurposing using supervised and unsupervised
learning approaches, achieving a predictive accuracy increase of 22% on benchmark datasets.
Developed a cloud-native architecture on Google Cloud Platform (GCP) leveraging Kubernetes for scalable model training and inference,
reducing end-to-end model deployment time by 40% and enabling continuous experimentation.
Integrated SQL pipelines to efficiently preprocess and query multi-modal biomedical datasets, enabling rapid retrieval of structured and
unstructured data for downstream AI reasoning.
Operationalized NLP-driven biomedical chatbots using transformer architectures and LangChain frameworks to provide researchers with
interactive, context-aware insights, accelerating literature search and experimental planning by 30%.
Formulated and fine-tuned transformer models using Hugging Face for biomedical text understanding, enabling automated literature
summarization and hypothesis extraction, reducing research effort by 40% while maintaining 95% semantic accuracy across 10K+ articles.
Conducted end-to-end R&D on multi-agent reasoning systems that combine supervised learning, unsupervised clustering, and reinforcement
learning to simulate complex biological interactions, contributing to three peer-reviewed publications in computational biology.
Optimized AI model performance and resource utilization on GCP by leveraging distributed training, mixed-precision computation, and realtime monitoring dashboards, improving inference efficiency by 25% while maintaining model accuracy on large-scale biomedical datasets.
2021 — 2023
2021 — 2023
India
Programmed and deployed predictive models for 5G network traffic and customer churn using Python, PyTorch, and ensemble methods
(Random Forest, XGBoost, LightGBM), achieving 92% accuracy and reducing network downtime forecasting errors by 28%.
Devised and fine-tuned BERT-based NLP pipelines for analyzing telecom customer interactions, leveraging LLM embeddings to classify service
requests, improving automated ticket resolution by 35% while reducing manual triage workload.
Implemented end-to-end CI/CD pipelines using Docker and AWS SageMaker for scalable model training and deployment, reducing model
release cycle time from 14 days to 5 days across multiple environments.
Built real-time analytics pipelines on AWS Cloud integrating MongoDB and time-series forecasting models to predict network load and optimize
5G bandwidth allocation, processing 2M+ traffic events daily, improving network utilization by 18%.
Performed hyperparameter optimization using Optuna and Ray Tune for deep learning and ensemble models, boosting predictive model F1
scores by 12% and ensuring robustness across diverse telecom datasets
Established Responsible AI practices, including bias detection, fairness evaluation, and model explainability in production pipelines, ensuring
compliance with regulatory standards while maintaining high model performance across telecom and biomedical datasets.
Architected comprehensive model validation and unit testing frameworks to ensure production reliability, including statistical performance
monitoring, drift detection, and reproducibility of results in cloud deployments.
Collaborated with cross-functional teams to integrate ML models with telecom APIs, enabling personalized service recommendations and
automated analytics dashboards, driving a 22% increase in customer engagement and revenue optimization.
Education
California State University-San Bernardino
Master's Degree
R.V.R. & J.C. College of Engineering