Role Overview

We are seeking a Graduate AI / ML Engineer (LLM Research & Fine-Tuning) with strong research exposure and hands-on experimentation experience in Large Language Models (LLMs). This role is ideal for candidates coming from research internships, academic projects, or thesis work, who want to apply cutting-edge ML research to real-world systems.

Key Responsibilities

• Experiment with and fine-tune LLMs using techniques such as LoRA, QLoRA, PEFT, instruction tuning, and related methods.

• Work on dataset preparation, including cleaning, preprocessing, anonymization, and licensing considerations.

• Design and run ML experiments and evaluations, tracking metrics using tools like MLflow or similar.

• Assist in deploying and testing models using inference or serving frameworks (e.g., vLLM, AWS Bedrock, or equivalent).

• Contribute to RAG pipelines, embeddings, and tool-augmented LLM workflows.

• Collaborate with senior engineers, researchers, and product teams to convert research ideas into prototypes.

• Follow model safety, compliance, and responsible AI practices.

• Stay up to date with the latest LLM research, papers, and open-source advancements.

Required Skills & Qualifications

• Bachelor’s degree in Computer Science, AI, ML, or a related field (Master’s preferred but not required).

• Strong foundation in machine learning fundamentals and applied ML concepts.

• Research experience through thesis work, academic projects, internships, or publications.

• Proficiency in Python for ML experimentation and prototyping.

• Ability to communicate research findings clearly and collaborate effectively in a team environment.

Must Have

• Hands-on experience with LLMs through academic, research, or personal projects.

• Familiarity with PyTorch, Hugging Face, or similar ML frameworks.

• Experience working with datasets and ML experimentation workflows.

• Understanding of parameter-efficient fine-tuning techniques (LoRA / QLoRA / PEFT).

• Working knowledge of Git and basic software engineering best practices.

• Strong curiosity, attention to detail, and a growth-oriented mindset.

Why join us:

• We hire for talent density — people who elevate our engineering and research culture.

• Work on real-world AI problems where applied research directly impacts production systems.

• Opportunity to grow from research-focused experimentation into production-grade AI engineering.

Our engineering culture:

• The How and Why: Why We’re Here  How We Challenge Ideas  How We Work Together
• Advanced training program: Learning @ Carbonteq
• Transparent growth paths: Progression Framework
• Our Open Source & Internal Tools

Perks:

🏥 Comprehensive Health Insurance
🏋️ Premium Gym Membership
📚 Dedicated Learning & Development Budget
💰 Annual Performance-Based Increments & Bonuses
🍕 In-house Meals (Lunch + Dinner)
🎮 Game Area & Sports Activities
🎉 Annual Trip & Monthly Recreational Activities
🎤 Annual Dinner with Entertainment

Details:
📍 Onsite – DHA Phase 5, Lahore
🗓 Mon–Fri | ⏰ 12 PM – 9 PM PKT