AI Developer — Onsite, Sialkot Office

FabTechSol · Sialkot, Pakistan

FULL TIME

Job Description

FabTechSol is building an A-class AI engineering team at our Sialkot office.

We need developers with deep, production-level experience across the modern AI stack — from core ML and deep learning to LLMs, MLOps, generative AI, and responsible deployment. If you understand not just how to use AI tools but how and why they break, we want to talk.

What We're Looking For

Depth beats familiarity — we hire for mastery, not buzzwords.

We're not hiring someone who has watched tutorials on GPT wrappers. We need engineers who understand model internals, can debug drift and hallucinations, build production ML pipelines from scratch, and ship AI systems that work reliably at scale.

The ideal candidate combines strong technical foundations (mathematics, algorithms, software engineering) with deep specialization in one or more areas of modern AI — whether that's LLMs, computer vision, reinforcement learning, or MLOps. You'll work across the full lifecycle: research, prototyping, training, deployment, monitoring, and iteration.

Skill Framework

You don't need to be an expert in every single item — but you should have strong coverage across these categories and deep expertise in at least two.

Core Technical Foundations

Apache Spark, Hadoop, Kafka — pipeline design and management
Algorithms & data structures for scalable solutions

Advanced AI & Specializations

LLMs & NLP — tokenization, embeddings, fine-tuning (LoRA, adapters), RAG
Prompt engineering — structured input design, hallucination mitigation
Reinforcement learning — reward modeling, policy optimization, RLHF
Docker, Kubernetes for scalable AI deployments
Big data at scale — real-time streams, distributed training, feature stores

Cognitive & Problem-Solving

First-principles thinking — breaking down novel problems from scratch
Systems thinking — understanding how AI components interact in larger ecosystems
Adaptability — continuously changing tools and frameworks as the field evolves
Debugging complex models — diagnosing bias, drift, hallucinations, brittle reasoning
Empathy & user focus — understanding real user problems worth solving
Cross-disciplinary communication with data scientists, PMs, and engineers
Ethics & responsible AI — bias detection, fairness, transparency, regulatory awareness
Continuous learning mindset — stagnation is disqualifying
Documentation & knowledge sharing — team knowledge scales beyond individuals

Team Role Matrix

LLM/GenAI Specialist — foundation models, RAG, fine-tuning, prompt systems
AI Product/Systems Architect — translating business problems into AI design
AI Ethics & Safety Lead — bias auditing, safety controls, compliance

Apply for This Role

Application Form

Fill out the form below. We review every application carefully. Only candidates with verifiable AI engineering experience will be considered.

Personal Information

Experience & Engagement

Years of Experience *

Preferred Engagement *

Work Arrangement *

Availability *

Primary AI Specialization(s) * — select all that apply Core Technical Foundations Advanced AI & Specializations MLOps & Systems Engineering Cognitive & Problem-Solving Soft Skills & Collaboration Team Role Matrix

Preferred ML Stack * — select all that apply PyTorch TensorFlow JAX Scikit-learn Other

Preferred Cloud * — select all that apply AWS GCP Azure On-premise/VPS No preference

Technical Details

Key Skills * (comma-separated)

LinkedIn Profile

Hugging Face / Kaggle / Papers with Code

Production AI Projects * (2-3 required)

Research & Open-Source Contributions

Upload CV (PDF or Word, max 10MB)

Experience Confirmations *

All six must be confirmed to be considered. Check every item that applies to your actual experience.

Core Technical Foundations — I have production experience with Python, ML frameworks (TensorFlow/PyTorch), and strong mathematical fundamentals

Advanced AI & Specializations — I have built and deployed LLM-based applications, generative AI, computer vision, or reinforcement learning systems

MLOps & Systems Engineering — I have hands-on experience with model versioning, CI/CD for ML, containerized deployments, and cloud platforms (AWS/GCP/Azure)

Cognitive & Problem-Solving — I can demonstrate first-principles thinking and debug complex models (bias, drift, hallucinations) in production

Soft Skills & Collaboration — I communicate effectively across technical and non-technical teams and care about responsible AI practices

Team Role Matrix — I can identify which AI team role(s) I best fit (ML Research, MLOps, Data Engineering, LLM/GenAI, Systems Architect, or AI Ethics/Safety)

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