AI Engineer

We are looking for a Junior AI Engineer (Generative AI / LLM) who is eager to learn and has early hands-on experience in training or fine-tuning models (from coursework, thesis, or personal projects).

This role is suitable for fresh graduates who want to grow into an LLM Engineer through real experimentation and product-focused development.

Key Responsibilities :

• Assist in fine-tuning pre-trained models (LLM or other deep learning models)
• Prepare datasets for training (cleaning, formatting, simple evaluation)
• Run training experiments and help monitor results
• Support optimization of training workflows (batching, GPU usage, etc.)
• Build simple APIs for model serving (FastAPI or similar)
• Participate in experimentation and model improvement cycles
  

Must-Have Requirements  :

• Basic to intermediate Python (OOP understanding)
• Hands-on experience with PyTorch or similar framework (from project / thesis / coursework)
• Understanding of basic deep learning concepts (training loop, loss function, dataset)
• You should have at least done ONE of the following:
• Fine-tuned a model (any scale, including small models or academic projects)
• Built a deep learning project involving training (not just inference)
• Completed a thesis/project involving NLP / deep learning
  

You should be able to explain:

• What model you used
• What data you trained on
• What changed after training (even simple metrics or observations)
• Basic understanding of REST API (FastAPI is a plus)
• Strong willingness to learn and experiment
  

Nice to Have :

• Exposure to LLM / Transformer concepts (attention, tokenization)
• Familiarity with Hugging Face (Transformers / Datasets)
• Awareness of fine-tuning methods (LoRA, PEFT — even theoretical)
• Experience with small-scale LLM or NLP projects
• Experience participating in AI competitions / research / bootcamps