About Us

We are building transformer models focused on multilingual translation and custom transformer architectures. Our team works on large-scale NLP and transformer-based models with a strong focus on research, experimentation, model optimization, and production-grade AI systems.
We are looking for a highly technical Data Scientist who is passionate about developing and improving AI/ML models, working on transformer architectures, and contributing to advanced NLP research and development.

This is a core engineering and research role — not a prompt engineering or API integration role.
Role Overview

As a Data Scientist, you will work on the training, fine-tuning, evaluation, and optimization of transformer-based NLP systems and LLMs. You will collaborate closely with engineering and research teams to build scalable AI models and contribute to the development of advanced multilingual AI solutions.

You should be comfortable working with model training pipelines, datasets, tokenization techniques, transformer architectures, and GPU-based training environments.



A solid interest in experimentation, model performance improvement, and real-world AI deployment is highly valued.

Key Responsibilities

Lead the architecture and development of transformer-based AI systems
Drive technical direction for NLP, LLM, and multilingual AI initiatives
Mentor and guide junior ML engineers and researchers
Train and fine-tune transformer models on large-scale custom datasets
Work on Seq2Seq / encoder-decoder architectures for translation and text generation
Optimize model performance using LoRA, QLoRA, PEFT, quantization, and distributed training techniques
Design tokenization pipelines using BPE / SentencePiece
Evaluate models using BLEU, perplexity, accuracy, and custom benchmarks
Collaborate with platform teams for GPU infrastructure and scalable deployments

Required Qualifications

2+ years of experience in Data Science / Machine Learning / NLP
Strong hands-on expertise in Tran

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