Manas Nayak
@manasnayak1
Software engineer specializing in LLM/GenAI, backend services, and production-ready AI tooling.
What I'm looking for
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
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.
Research Associate
Centre of Artificial Intelligence and Robotics
May 2024 - Jul 2024 (2 months)
Designed 5+ GenAI/LLM tools and exposed model calls as REST APIs that improved content creation 40% and reduced onboarding time 15%; authored latency/accuracy evaluation scripts and API documentation.
Education
Degrees, certifications, and relevant coursework
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.
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%).
Availability
Location
Authorized to work in
Salary expectations
Social media
Job categories
Skills
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