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AI LLM / NLP Tech Lead (On-site) — Islamabad

AI LLM / NLP Tech Lead (On-site) — Islamabad

VulsightIslamabad, Islamabad Capital Territory, Pakistan
10 days ago
Job description

AI LLM / NLP Tech Lead (On-site) — Islamabad

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Start : ASAP

About VulSight

Location : Islamabad, Pakistan — on-site, full-time

Team : Engineering (AI / Research)

Start : ASAP

VulSight is a Web3 security firm helping teams ship safely across Move, Rust, and EVM ecosystems. We’ve delivered hundreds of assessments in traditional cybersecurity and Web3, and we’re now building NLP / LLM-driven agents that reason over code, audits, and on-chain data to catch bugs earlier and accelerate reviews.

The Role

You’ll own our AI roadmap end-to-end— research → prototyping → productization → team leadership . Your focus is on LLMs, NLP, and AI agents (tool use, planning, retrieval, evaluation) grounded in solid ML fundamentals . Blockchain / security knowledge is a plus.

What you’ll do

  • Design & ship agentic systems that reason over smart-contract code (Move / Solidity), diffs, on-chain data, and prior audits; perform retrieval, analysis, test generation, and triage.
  • Build RAG pipelines (indexing, chunking, retrievers), long-context strategies, tool calling, and multi-step planning (e.g., LangGraph-style flows).
  • Own LLM evaluation : golden sets, style metrics, rubric-based grading, and production feedback loops (hallucination detection, safety, guardrails).
  • Lead prompt engineering and model customization (SFT, LoRA / QLoRA, instruction tuning, RLAIF / RLHF where appropriate).
  • Stand up inference infrastructure (vLLM / TGI / Triton), latency & cost optimization, caching, and observability (tracing, telemetry, error budgets).
  • Curate high-quality datasets from public repos, audits, and on-chain sources; build labeling and synthetic-data pipelines.
  • Collaborate with security researchers to turn workflows into auditor-grade copilots (invariant mining, property / test generation, patch suggestions).
  • Hire, mentor, and lead a small on-site AI team; drive roadmap, rituals, and delivery quality.

Must-have qualifications

  • Strong Python and at least one major DL framework (PyTorch preferred).
  • 4–8+ years in ML / AI; 2+ years owning end-to-end ML / LLM projects or leading small teams.
  • Hands-on with LLM application stacks : retrieval (FAISS / Milvus / pgvector), embeddings, tool use / function-calling, streaming, telemetry.
  • Experience with agent orchestration (e.g., LangGraph, LangChain, LlamaIndex—or custom graphs) and productionizing LLM apps.
  • Solid NLP fundamentals (tokenization, sequence modeling, evaluation), plus prompting & instruction-tuning best practices.
  • MLOps / inference : serving (vLLM / TGI), batching, quantization, containerization, CI / CD for models, and experiment tracking.
  • Clear product sense : turning fuzzy research ideas into shippable features with measurable impact.
  • Nice to have

  • Blockchain / Web3 familiarity (Move, Solidity, Rust), static / dynamic analysis, or prior security / audit exposure.
  • Program analysis / compilers / AST work; code-intelligence or LLM-for-code experience.
  • Fine-tuning at scale (LoRA, PEFT), dataset distillation, or RLHF / RLAIF pipelines.
  • Systems performance chops (CUDA / Triton, vectorization) or search / retrieval research.
  • Experience with on-chain data tooling (Aptos / Sui / EVM nodes, indexers, subgraphs).
  • Why join

  • Real users, real problems : your work lands in auditors’ hands immediately.
  • Ownership : greenfield architecture with the mandate to do it right.
  • Learning loop : tight feedback with senior security researchers and real codebases.
  • Compensation

    Competitive salary + equity . Hardware and learning budget provided.

    Seniority level

  • Mid-Senior level
  • Employment type

  • Full-time
  • Job function

  • Engineering and Information Technology
  • Industries
  • Blockchain Services
  • #J-18808-Ljbffr

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