Associate AI Engineer – LLM & Computer Vision (Onsite, Karachi, PKR Salary)

HR POD Careers; Karachi Division; On-site; PKR 900,000 - 1,400,000; Full time

Job summary

HR POD Careers is seeking a junior AI/ML talent to help build LLM-based apps like chatbots and RAG systems. You will help with data prep, model evaluation, and basic inference pipelines while collaborating with engineering, product, and data teams.

Ideal candidates bring 0–2 years of experience, strong Python fundamentals, and familiarity with PyTorch/TF/Scikit-learn, LLM concepts, and cloud AI environments. A learning mindset and documentation discipline are essential.

Qualifications

• Fresh to 2 years of AI/ML experience with Python fundamentals.
• Familiarity with PyTorch, TensorFlow, or Scikit-learn and basic LLM concepts.
• Experience with computer vision, data preprocessing, and basic model metrics.
• Experience with Hugging Face, LangChain, OpenAI APIs, RAG and vector databases.
• Exposure to cloud AI environments.
• Academic or portfolio projects involving LLMs, computer vision, or multimodal AI.
• Willingness to experiment under guidance and a strong learning mindset.
• Structured and clean implementation approach, curiosity, documentation discipline, and collaboration.

Responsibilities

• Assist in building LLM-based applications such as chatbots, RAG systems, and AI assistants.
• Support data preprocessing, labeling, and model evaluation workflows.
• Implement basic inference pipelines and integrate AI APIs.
• Assist with prompt engineering, experimentation, and model output evaluation.
• Work with embeddings, vector databases, and retrieval workflows.
• Support computer vision experiments and image or video processing tasks.
• Document experiments, datasets, results, and implementation decisions.
• Collaborate with software engineering, product, and data teams.

Skills

Python

PyTorch

TensorFlow

Scikit-learn

LLMs

Prompt engineering

RAG

Vector databases

Hugging Face

LangChain

OpenAI APIs

Cloud AI

Computer vision

Data preprocessing

Multimodal AI

Documentation

Tools

Hugging Face

LangChain

OpenAI APIs

Vector databases

Job description

• Fresh to 2 years of AI/ML experience, including academic or personal projects, with strong Python fundamentals.
• Familiarity with PyTorch, TensorFlow, or Scikit-learn, along with a basic understanding of LLMs, prompt engineering, and evaluation.
• Exposure to computer vision fundamentals, data preprocessing, and basic model metrics.
• Exposure to Hugging Face, LangChain, OpenAI APIs, or similar tools, with familiarity with RAG and vector databases.
• Exposure to cloud AI environments.
• Academic or portfolio projects involving LLMs, computer vision, or multimodal AI.
• Strong learning mindset and willingness to experiment under guidance.
• Structured and clean implementation approach, with curiosity, documentation discipline, and the ability to collaborate cross-functionally.

Requirements:

• Fresh to 2 years of AI/ML experience, including academic or personal projects, with strong Python fundamentals.
• Familiarity with PyTorch, TensorFlow, or Scikit-learn, along with a basic understanding of LLMs, prompt engineering, and evaluation.
• Exposure to computer vision fundamentals, data preprocessing, and basic model metrics.
• Exposure to Hugging Face, LangChain, OpenAI APIs, or similar tools, with familiarity with RAG and vector databases.
• Exposure to cloud AI environments.
• Academic or portfolio projects involving LLMs, computer vision, or multimodal AI.
• Strong learning mindset and willingness to experiment under guidance.
• Structured and clean implementation approach, with curiosity, documentation discipline, and the ability to collaborate cross-functionally.

Responsibilities:

• Assist in building LLM-based applications such as chatbots, RAG systems, and AI assistants.
• Support data preprocessing, labeling, and model evaluation workflows.
• Implement basic inference pipelines and integrate AI APIs.
• Assist with prompt engineering, experimentation, and model output evaluation.
• Work with embeddings, vector databases, and retrieval workflows.
• Support computer vision experiments and image or video processing tasks.
• Document experiments, datasets, results, and implementation decisions.
• Collaborate with software engineering, product, and data teams.