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Manas NayakMN
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Manas Nayak

@manasnayak1

Software engineer specializing in LLM/GenAI, backend services, and production-ready AI tooling.

India
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What I'm looking for

I seek roles building production LLM/GenAI systems with strong engineering practices, CI/CD, observability, and collaborative Agile teams for impact and growth.

I am a software engineer focused on building production-quality LLM and GenAI applications, with hands-on experience in Python, PyTorch, and REST services.

At Intel I engineered LLM-driven automation that migrated 100,000+ lines of code and shipped REST services and internal tools, cutting manual validation by 60–80% and enabling multiple teams to self-serve conversions.

As a research associate at DRDO's CAIR I designed multiple GenAI/LLM tools, exposed model calls as REST APIs, and authored latency and accuracy evaluation scripts while participating in Scrum ceremonies with researchers.

I prioritize inference performance, CI/CD integration, and observability (logging/metrics) to deliver reliable, test-covered systems that scale in production environments.

Experience

Work history, roles, and key accomplishments

Intel Corporation logoIC

AI Intern

Intel Corporation

Feb 2025 - Jul 2025 (5 months)

Engineered LLM-driven automation that migrated 100,000+ LOC and shipped as REST services, reducing manual validation 60–80% and enabling 3 teams to self-serve; built an AI code-review agent integrated into CI/CD to reduce review iterations.

Education

Degrees, certifications, and relevant coursework

National Institute of Technology Rourkela logoNR

National Institute of Technology Rourkela

Bachelor of Technology, Electronics and Communication Engineering

2021 - 2025

Bachelor of Technology in Electronics and Communication Engineering completed at NIT Rourkela with coursework and projects in AI/ML, systems, and software engineering.

DP

DAV Public School, Pokhariput

Matriculation and Intermediate, Science and Mathematics

2007 - 2020

Completed Matriculation and Intermediate in Science and Mathematics with high marks (Matriculation 95.2% and Intermediate 95%).

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