About
Highly skilled Software Development Engineer with a strong foundation in AI/ML, cloud infrastructure, and distributed systems, demonstrated through impactful roles at Hyperbots Systems and UPL Ltd. Proven ability to optimize production environments, reduce cloud costs, and build resilient, high-performance systems, consistently delivering measurable results. Eager to leverage expertise in scalable solutions and advanced technologies to drive innovation in a dynamic tech environment.
Work
Hyperbots Systems Pvt. Ltd.
|Software Development Engineer
Bangalore, Karnataka, India
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Summary
Leads software development initiatives at a Finance AI Company, focusing on optimizing production environments, reducing cloud costs, and building high-performance distributed systems.
Highlights
Reduced deployment time by 50% through containerization of Spring Boot and ML workloads, automating CI/CD pipelines with Jenkins on AWS ECS and GCP GKE.
Engineered dynamic autoscaling solutions, reducing cloud costs by $40,000 by leveraging KEDA with GPU metrics, Kafka queue optimization, and enhanced observability via Prometheus.
Optimized Reactive Spring Boot ingestion, cutting database calls by 90% through re-architecting and implementing strategic batch processing to prevent connection overload during peak loads.
Developed a resilient Change Data Capture (CDC) pipeline, achieving sub-100 ms latency at 10K+ events/sec by streaming real-time updates from PostgreSQL and MongoDB into Elasticsearch using Debezium and Apache Kafka.
Developed scalable Spring Boot microservices with robust RESTful APIs, integrating a centralized Eureka server to streamline business operations through seamless service discovery.
UPL Ltd.
|Data Science Intern
Bangalore, Karnataka, India
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Summary
Automated the churn-prediction ML lifecycle and authored an MLOps reference architecture to enhance model training reliability and reduce cloud costs.
Highlights
Automated the end-to-end churn-prediction ML lifecycle using MLflow and Databricks, integrating GitHub Actions for CI/CD.
Authored a comprehensive MLOps reference architecture, significantly boosting reliability and cutting cloud costs for scalable model training.
TCS Research
|Deep Learning Researcher
Mumbai, Maharashtra, India
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Summary
Conducted research on optimizing gradient flows and co-authored a publication while benchmarking leading deep learning models.
Highlights
Conducted research on optimizing fixed-time convergence of gradient flows, co-authoring an internal publication.
Benchmarked leading deep learning models including ResNet, VGG, and Transformers in PyTorch, achieving 95% accuracy on CIFAR/MNIST datasets.
Education
Indian Institute of Technology Bombay
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B.Tech.
Aerospace Engineering
Grade: 8.21/10
Publications
Certificates
Machine Learning and Deep Learning Specialization
Issued By
Coursera (Andrew Ng)
Skills
Languages & Frameworks
C++, Python, Java, Spring Boot (Reactive).
Ops & Databases
Kafka, Docker, Kubernetes, Jenkins, Airflow, PostgreSQL, MongoDB, Elasticsearch.
Cloud Services
AWS (ECS, ECR, RDS, MSK, CloudWatch), GCP (GKE, VMs), Cloud Networking (VPC, VPN).
Data Science & ML
MLflow, Databricks, MLOps, Deep Learning, Computer Vision, NLP, PyTorch, ResNet, VGG, Transformers.
Tools & Methodologies
GitHub Actions, CI/CD, GMAT, Prometheus, KEDA, Debezium, Eureka.
Projects
Analytics Club & MnP Club Mentor
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Summary
Mentored students on Machine Learning and Data Science projects, overseeing their progress and fostering problem-solving skills.
IITB Student Satellite Program – Tech Team
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Summary
Contributed to the development of onboard systems software and telemetry integration for student satellite space missions.