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 Seq2 Seq / encoder-decoder architectures for translation and text generation
- Optimize model performance using Lo RA, QLo RA, PEFT, quantization, and distributed training techniques
- Design tokenization pipelines using BPE / Sentence Piece
- 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

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