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Re:Ask HN: Who wants to be hired? (October 2026) by Trakshan on Friday October 02, 2026 @10:04AM (#49933671)
Location: Noida, India (UTC+5:30)

Remote: Yes

Willing to relocate: Yes (would need visa sponsorship outside India)

Technologies: Python, TypeScript, SQL, FastAPI, Django REST Framework, Node.js, React, Next.js, PostgreSQL, SQLite, MongoDB, Cloudflare Workers, Docker, Linux. LLM systems: agents, tool calling, MCP, RAG, embeddings, BM25 retrieval, evals. Read and patched Java, Rust and C in open-source work.

Resume/CV: https://drive.google.com/file/d/1MK3XqvWlbDTq2l1MVm7yXGKiMfS...

GitHub: https://github.com/trakshan-mishra

Email: [email protected]

I build Python and TypeScript backends and the tooling around them, and I try to measure whether what I ship works.

DiffContext (https://pypi.org/project/diffcontext/) is a context-selection library for code LLMs. It cuts the context a model reads by a median 89% across 9 repos and 701 commits, and raised pass@1 from 5.5% to 25.8% on 128 tasks. It ships as a CLI and MCP server with 358 tests in CI, and I published a self-audit that retracted three of my own earlier claims.

Open source, every fix with tests: merged in Comet Opik (streaming wrappers were swallowing exceptions) and facebook/astryx (focus-trap bug). In review: apache/superset (approved), kubeflow/mcp-server (FastMCP 4 upgrade), bitcoindevkit/bdk_wallet (Rust, relative locktimes), and a Java/ClickHouse change in Opik. I also review PostgreSQL patches on CommitFest.

Before that: React front ends on Django REST and FastAPI back ends over PostgreSQL (cut API response times 35%), and FastAPI model serving at 150 req/s. Now building Python environments that AI agents are evaluated in.

M.Tech in AI & Data Science at IIT Patna, part-time.

Looking for backend, AI/LLM or full-stack roles. Can start immediately.

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