Now

What I'm focused on this month — last updated Jun 1, 2026.

Working on

Enhancing next js backend services with SQL and BigQuery for efficient data processing and improved API response latency.
Also working on bug fixes and performance optimizations for existing services, leveraging my full-stack JS/TS skills and cloud experience.

Learning

PyTorch fundamentals — tensors, autograd, training loops, testing loops, forward and backward passes, backpropagation, optimizers, and more.
Classification Neural Networks (CNNs) and transformer architectures for NLP tasks, setting up loss functions and optimization strategies.
Convolutional Neural Networks (CNNs), Data Loaders, confusion matrices, and evaluation metrics for image classification tasks.
Custom datasets, imagefolder structure, Data augmentation with torchvision.
Pytorch transfer learning
Transformer architecture, attention mechanisms, embeddings, encoders, decoders etc
LangChain agents and tool-calling patterns
Retrieval-Augmented Generation (RAG) pipelines with vector databases like FAISS
Also learning about prompt engineering best practices, few-shot prompting, and evaluation techniques for LLM applications.
Continuing to deepen my understanding of cloud-native architectures, containerization with Docker, and orchestration with Kubernetes.
Exploring Terraform for infrastructure as code and Jenkins for CI/CD automation to streamline development workflows.
Autoscaling groups and load balancing strategies on AWS and GCP to optimize application performance and cost-efficiency.
AWS ERC, ECS and container orchestration patterns for scalable deployments.
Monitoring and new relic for observability and performance optimization of cloud applications.
prometheus and grafana for monitoring and alerting in cloud environments.
Kubernetes concepts like namespaces, deployments, services, and ingress controllers for managing containerized applications at scale.

Location

India

This is a /now page — short snapshot of current focus, not a full activity log.