# Devanshu Gupta

> Seeking Full Time Opportunities for MLE, SDE roles 
| SDE @ Amazon | Building AI systems serving millions of customers

Location: New York, New York, United States
Profile: https://flows.cv/devanshugupta

I’m a Software Engineer (ML) at Amazon Prime Video, where I build large scale AI systems powering real time personalization for millions of users. My work spans embedding based retrieval and ranking, distributed backend services, and production ML pipelines optimized for low latency, high concurrency environments.

I specialize in turning research into reliable production systems from fine tuning LLMs and designing evaluation frameworks to shipping scalable microservices that support experimentation and measurable business impact. I care deeply about system design, performance, and building ML solutions that actually move product metrics.

With an MS in Computer Science from Arizona State University (2025), my focus is on applied machine learning, relevance systems and production AI. I’m particularly interested in roles at the intersection of backend engineering, large-scale ML, and intelligent systems.

## Work Experience
### Software Engineer (Machine Learning) @ Amazon
Jan 2025 – Present | New York, United States
Working on content delivery, personalization, and next-gen viewing experiences on Prime Video. Focussed on Ownership, Delivering results and Collaboration.

- Led Prime Video - Alexa service meeting 300 ms latency SLA and generating conversational voice text streaming LLM summarization processing 100K queries daily.
- Architected distributed microservices for ML inference, achieving 99.9% availability under high-concurrency production traffic.
- Optimized large-scale PyTorch inference pipelines, reducing P99 latency 3x through parallelization and memory-efficient caching.
- Designed feature gating framework to support controlled rollouts, A/B testing, repeatable evaluation of 10+ AI features
- Established REST API contracts, unit testing, and CI validation pipelines reducing regression defects 30% before release.
- Identified system bottlenecks and improved performance through scalable caching and service orchestration.

### Researcher @ Arizona State University
Jan 2025 – Present | Arizona, United States
Developed reasoning framework to enhance semi-structured & multi-modal Table QA.

### Teaching Assistant @ Arizona State University
Jan 2025 – Present | Arizona, United States
CSE 575: Statistical Machine Learning, Prof. Kookjin Lee
CIS 565: AI in Business, Prof. Julian Lehmann
CIS 508: Machine Learning in business, Prof. Asim Roy

### Data Engineer @ Tata Consultancy Services
Jan 2021 – Jan 2023 | Hyderabad
Built predictive models for demand forecasting cutting supply chain costs by $4M.

Designed big data pipelines & data models, that manage 1TB+ data in Azure Data lake and S3 buckets

### Research Intern @ Tata Consultancy Services
Jan 2021 – Jan 2021 | Hyderabad, Telangana, India
Built predictive models from employee KPI data, improving performance rating accuracy by 25% enabling data-driven evaluations.

### Machine Learning Engineer @ Affirmity
Jan 2020 – Jan 2020 | India
Collaborated with software development and marketing teams to develop enhanced solutions that meet client requirements for functionality, scalability and performance of a firm wide software.


## Education
### Master's degree in Computer Science
Arizona State University

### Bachelor of Technology in Computer Science
University Institute of Technology, RGPV


## Contact & Social
- LinkedIn: https://linkedin.com/in/devanshu0gupta

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Source: https://flows.cv/devanshugupta
JSON Resume: https://flows.cv/devanshugupta/resume.json
Last updated: 2026-04-05