Saurav Biswas
@sauravbiswas
M.Tech computer scientist specializing in ML, LLM fine-tuning, and automation testing.
What I'm looking for
I am an M.Tech computer scientist with hands-on experience in machine learning, LLM fine-tuning and deployment, automation using Playwright, and SDET practices. I have delivered production-oriented projects — from EEG image classification and crop prediction models to fine-tuning Phi-3-mini for a medical domain and deploying it on Hugging Face Spaces.
I combine practical engineering (PyTorch, Hugging Face, PEFT/LoRA, Playwright, Postman) with a results focus: automating workflows that cut manual effort by 80%, achieving high test coverage and defect detection, and building ML solutions with demonstrable accuracy and user impact. I enjoy mentoring, leading small teams, and contributing to open-source projects.
Experience
Work history, roles, and key accomplishments
Automation Intern
Oslash
Aug 2022 - Oct 2022 (2 months)
Automated ticket-booking workflow using Playwright, reducing manual processing by 80% and saving 0.5 hours per week through reusable scripts.
SDET Intern
Rakshul
Mar 2022 - Jun 2022 (3 months)
Executed 50+ manual test cases and 20+ Postman API collections achieving 90% coverage and identified 30+ defects to improve feature stability pre-release.
Education
Degrees, certifications, and relevant coursework
National Institute of Technology Durgapur
Master of Technology, Computer Science & Engineering
2024 -
Activities and societies: Qualified GATE 2024 (CSE + AI/ML); participated in college chess tournament.
Pursuing Master of Technology in Computer Science & Engineering with coursework and projects in machine learning, deep learning, and LLM applications.
Siddaganga Institute of Technology
Bachelor of Technology, Information Science
2018 - 2022
Grade: 7.27/10
Activities and societies: Teaching assistant for C Programming and Digital Logic labs; led student team activities and contributed to open-source projects.
Completed Bachelor of Technology in Information Science with projects in predictive modeling and deep learning, graduating with a CGPA of 7.27/10.
Tech stack
Software and tools used professionally
Availability
Location
Authorized to work in
Job categories
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