Hello!
I'm Avrodeep Pal ★
My focus sharpens around LLM Infrastructure and Reasoning Models
Reading DeepSeek-R1 · Building ReasoningPractice
Hello!
Reading DeepSeek-R1 · Building ReasoningPractice
Experience

Software Development Engineer · Full-Time
LLM Serving & vLLM Migration: Delivered ~17x LLM throughput on staging by migrating serving to vLLM, after a controlled benchmark of 7 serving setups showed the serving software, not the GPU, was the bottleneck: 100 mixed requests dropped from 213s to 12.6s. 64 concurrent streams now finish in 2.2s where the old server froze past 40, with GPU memory budgeting enforced before any deploy and 59 of 59 live checks passing. The benchmark also surfaced 8 platform bugs, all fixed, and produced 13 ranked recommendations for leadership.
DeepSeek V4 Flash Bring-Up: Scored 92.5/93 on a 10-phase acceptance suite across ~20,500 requests while bringing up a large mixture-of-experts model on staging with tensor and expert parallelism, extending the platform to manage multi-GPU replicas, backed by 463 unit tests. Recalled 48 of 48 planted facts in contexts up to ~260K tokens, handled 100 simultaneous calls in 18.25s, ran a 30-minute soak with zero restarts, and recovered from a killed GPU process on its own in 88s. Deploys dropped from an 8-minute reload to 3.6 minutes with the model left running.
Security, Reliability & Deployment: Audited a ~114,000-line Python platform by tracing request paths end to end, then mapped failure modes across core subsystems, delivering ranked findings and phased fix plans for leadership. Hardened input and file handling with 80+ regression assertions and restored correct HTTP status codes so monitoring and retries work as intended. Reworked deployment tooling across 100+ files, removing ~573 duplicate lines, verified by 32 offline tests and parity across 123 commands; now in validation ahead of rollout.
Image-to-Video Optimisation & GPU Debugging: Sped up image-to-video generation ~3.5x (398.7s to ~115s) by stacking and measuring each optimisation, including FP8 and torch.compile. Traced broken multi-GPU output to silent data corruption in direct GPU-to-GPU copies, reproduced with no model loaded (40 of 40 transfers corrupt, 0 of 40 through host memory), then fixed it by routing copies through the CPU. Also diagnosed thermal throttling and handed it to the hardware team with evidence.

Python Developer Intern · Internship
File Transfer Architecture Redesign: Achieved a 470x reduction in gateway RAM on large uploads (1,225MB to 2.6MB for a 300MB file) by overhauling the pipeline with streaming multipart handling and temp-file spooling with integrity verification. Built frontend concurrency controls and cache batching that took a 200-file operation from 200 storage writes to 1, eliminating freezes during multi-file operations. Moved blocking sync work off the event loop with thread pooling, so large repository syncs no longer stall the server.
Medical AI Ensemble & Hardware Benchmarking: Built a multi-modal ensemble reaching 84% accuracy on skin lesion classification from 39,231 cleaned images, beating a fine-tuned 400M-parameter foundation model by 2.8 points, and deployed it on the platform. Designed a hardware benchmarking framework across 18 vision and text models, measuring CPU-to-GPU speedups of 9x to 327x and documenting the conditions each figure holds under. Set up vision, ASR, and TTS models on server GPUs as multi-modal use cases.
RAG Backend, Code Checker & Microservices: Built an end-to-end RAG backend covering ingestion, 5 embedding models, token-aware chunking and HNSW semantic search, reaching a 0.93 similarity score in a directional test on a technical document. Built a static analysis + LLM engine that detects SQL injection, RCE, and XSS with intent-aware parsing and plain-English explanations. Worked on Dockerized FastAPI microservices with role-based access control and a layered request pipeline.
Workflow Platform & Quality Ownership: Shipped publicly documented workflows across 6+ domains, including Legal Helper, Finance Helper with 12 analysis types, and Card Recommendation across 80+ cards. Led the upgrade from custom-only nodes to a reusable workflow system built from generic building blocks, making new workflows much quicker to build and opening them to non-technical users. Own the alpha testers' regression suite, run after every frontend or backend push.
Skills
Projects

Syntactics and Semantics is how words mean. On that note, the project pivots around Bangla!

Attention is All YOU Need, and I will see to its references.

The rarer the frauds, the pricier. Keen to algos, time and reasonings, lets ensemble!

Analyze and Visualize tonight! Explote 8 ML ALgos compete to predict Loan Approval Status!

AI-powered Recruitment aid for Personalization and Automating Placement Communication!

Stock Market Forecasting powered by Deep Learning! Compare ReLU and GELU Performance while Accuracy skyrockets!

Save some Clicks and lot more Trees! Visit the Ultimate Online Book Store for Learners!
About

Developer by skill, Student by status, Problem Solver by spirit. Obsessed with clean UIs, clever logic and LLMs that actually make sense.
A huge believer in Parkinson’s Law, clean commit histories and non-caffeinated debugging (prefer black-tea @ midnight).
Currently on a mission to blend design and AI to build things that matter.
Jadavpur University, Kolkata
CGPA : 8.90 /10 (2024 - 2026)
Placement Coordinator | WBJECA'24 GMR 2
Barrackpore Rastraguru Surendranath College (affiliated to West Bengal State University)
CGPA: 9.91 /10 (2021 - 2024)
WBSU Rank 1
Score: 95.75% (2019 - 2021)
Score: 91.80% (upto 2019)
Contact
I'd love to hear from you! Let's create something great together.
Building AI systems in production, reading papers on reasoning models in parallel. Always open to a good technical conversation - reach out if you're working on something interesting.