AI LLM/NLP Tech Lead

1 week ago

Islamabad, Islamabad, Pakistan Vulsight Full time $104,000 - $130,878 per year

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

Team:
Engineering (AI / Research)

Start:
ASAP

About VulSight

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.

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