Ayush A Bansal profile photo 1 on Tal

Ayush A Bansal

Backend & MLOps Engineering

Delhi

1+ year of work experience

HyperVerge
Jul 20262 mosPresent

HyperVerge
Jan 20267 mosJul 2026

Backend engineer focused on performance optimization, ML model serving, and cloud infrastructure for production inference systems. • Identified a 2.5–3x throughput gain and ~$2,000 in projected infrastructure cost savings (proof-of-concept stage) through an independent bottleneck analysis on GPU-accelerated inference workloads • Cut production API p99 latency by 250ms and increased core inference service throughput by 1.5x by profiling backend services and refactoring execution paths across Python and Node.js layers • Accelerated model execution by integrating Triton Inference Server with GPU acceleration and JIT compilation (TorchScript/XLA), and improved MLOps efficiency by benchmarking preprocessing pipelines for latency and resource load • Reduced Docker image size and build time by 40–50% by redesigning the containerization strategy; managed AWS infrastructure (EC2, S3, SNS, CloudWatch) and Terraform-provisioned environments for reproducible deployments
MyNextDeveloper
Jun 20252 mosJul 2025

During my internship at MyNextDeveloper, I worked as a Fullstack Engineer, contributing to both the frontend and backend of a live learning and collaboration platform using Next.js and TypeScript. On the frontend, I focused on building dynamic and interactive UIs using advanced React Hooks, React Flow, and custom reusable components. I developed a flowchart-based learning path editor using React Flow, implementing features like draggable custom nodes, dynamic node creation on edge connection, and cycle prevention. On the backend, I designed and optimized complex MongoDB aggregation pipelines to handle nested queries and improve performance. I also handled API development, server-side logic, and integrated Amazon S3 for media uploads and secure file handling. One of my key contributions was the end-to-end R&D and implementation of live transcription using the Web Speech API. This included: Real-time speech-to-text streaming with proper chunk handling, Generating relative VTT (WebVTT) timecodes synced to the start of each live session, Persisting transcripts securely via backend APIs on tab close/exit, And optimizing performance to avoid redundant re-renders and resource leaks. Throughout the internship, I focused on code optimization, modularity, and clean architecture to ensure scalable and maintainable systems across the stack.
Dec 20242 mosJan 2025

RawCubes | 1-month Internship Developed and maintained features using the MERN stack (MongoDB, Express.js, React.js, Node.js). Built and integrated RESTful APIs to enable smooth communication between frontend and backend. Worked on database operations, state management, and improved UI responsiveness and performance.
NexTurn
Jun 20242 mosJul 2024

Remote

Nexturn | 2-month Internship Contributed to a major frontend migration by transitioning the entire CSS architecture from Tailwind CSS to Material UI, aligning with client requirements for a more component-driven design system. Developed reusable React components to support new feature integrations and enhance UI scalability. Utilized useRef effectively across various components to manage references and optimize performance, replacing unnecessary state-based approaches. Actively resolved linter errors, improved code quality, and participated in code refactoring to enhance maintainability and consistency. Built a shared utilities library to centralize common logic and reduce redundancy across the codebase.

Ayush’s AI Stack

anthropic apis
anthropic apis
claude code
claude code
claude
claude
codex
codex

Education

jaypee institute of information technology

Bachelor of Technology - BTech, Computer Science

jaypee institute of information technology

20224 yrs2026

sachdeva public school

200814 yrs2022

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Headline

Backend & MLOps Engineering

About

“Don’t have DREAMS. Have GOALS.” I'm a Backend & MLOps Software Engineer, passionate about building scalable, production-grade systems and contributing to high-impact engineering teams. A Computer Science and Engineering graduate from Jaypee Institute of Information Technology (JIIT), with hands-on experience in production-level systems, latency optimisation, and infrastructure engineering. My work spans backend engineering and MLOps, including AWS infrastructure, GPU acceleration, CI/CD tooling, and cost/capacity optimisation alongside a strong foundation in full-stack development, spanning RESTful API development, database optimisation, and scalable web applications. I thrive in collaborative, fast-paced environments and excel at problem-solving, system optimization, and quickly adapting to new technologies. Whether it's optimising infrastructure at scale or architecting end-to-end solutions, I bring creativity, dedication, and a growth mindset to every project.

Location

Delhi

AI stack

anthropic apis

claude code

claude

codex

Work experience

SDE1 at HyperVerge, Jul 2026 - Present · 2 mos

SDE Intern at HyperVerge, Jan 2026 - Jul 2026 · 7 mos, Backend engineer focused on performance optimization, ML model serving, and cloud infrastructure for production inference systems. • Identified a 2.5–3x throughput gain and ~$2,000 in projected infrastructure cost savings (proof-of-concept stage) through an independent bottleneck analysis on GPU-accelerated inference workloads • Cut production API p99 latency by 250ms and increased core inference service throughput by 1.5x by profiling backend services and refactoring execution paths across Python and Node.js layers • Accelerated model execution by integrating Triton Inference Server with GPU acceleration and JIT compilation (TorchScript/XLA), and improved MLOps efficiency by benchmarking preprocessing pipelines for latency and resource load • Reduced Docker image size and build time by 40–50% by redesigning the containerization strategy; managed AWS infrastructure (EC2, S3, SNS, CloudWatch) and Terraform-provisioned environments for reproducible deployments

Software Developer Summer Intern at MyNextDeveloper, Jun 2025 - Jul 2025 · 2 mos, During my internship at MyNextDeveloper, I worked as a Fullstack Engineer, contributing to both the frontend and backend of a live learning and collaboration platform using Next.js and TypeScript. On the frontend, I focused on building dynamic and interactive UIs using advanced React Hooks, React Flow, and custom reusable components. I developed a flowchart-based learning path editor using React Flow, implementing features like draggable custom nodes, dynamic node creation on edge connection, and cycle prevention. On the backend, I designed and optimized complex MongoDB aggregation pipelines to handle nested queries and improve performance. I also handled API development, server-side logic, and integrated Amazon S3 for media uploads and secure file handling. One of my key contributions was the end-to-end R&D and implementation of live transcription using the Web Speech API. This included: Real-time speech-to-text streaming with proper chunk handling, Generating relative VTT (WebVTT) timecodes synced to the start of each live session, Persisting transcripts securely via backend APIs on tab close/exit, And optimizing performance to avoid redundant re-renders and resource leaks. Throughout the internship, I focused on code optimization, modularity, and clean architecture to ensure scalable and maintainable systems across the stack.

MERN Stack Developer Intern at Rawcubes, Dec 2024 - Jan 2025 · 2 mos, RawCubes | 1-month Internship Developed and maintained features using the MERN stack (MongoDB, Express.js, React.js, Node.js). Built and integrated RESTful APIs to enable smooth communication between frontend and backend. Worked on database operations, state management, and improved UI responsiveness and performance.

Frontend Intern at NexTurn, Jun 2024 - Jul 2024 · 2 mos, Remote, Nexturn | 2-month Internship Contributed to a major frontend migration by transitioning the entire CSS architecture from Tailwind CSS to Material UI, aligning with client requirements for a more component-driven design system. Developed reusable React components to support new feature integrations and enhance UI scalability. Utilized useRef effectively across various components to manage references and optimize performance, replacing unnecessary state-based approaches. Actively resolved linter errors, improved code quality, and participated in code refactoring to enhance maintainability and consistency. Built a shared utilities library to centralize common logic and reduce redundancy across the codebase.

Education

Bachelor of Technology - BTech, Computer Science, jaypee institute of information technology

sachdeva public school