Research Scientist - Vision Language Model

We are a dedicated research lab for building, understanding, using, and risk-managing foundation models. Our mandate is to advance research, nurture the next generation of AI builders, and drive transformative contributions to a knowledge-driven economy. 

• Experience working with large language models and/or vision-language models, including pre-training, fine-tuning, evaluation, or inference.

• Strong Python and PyTorch development skills for large-scale machine learning research.

• Experience with distributed training systems and large-scale model optimization.

• Familiarity with multimodal datasets and data processing pipelines involving images, text, and video.

• Understanding of modern deep learning architectures, including Transformers, attention mechanisms, and multimodal fusion techniques.

• Experience with ML infrastructure, including model evaluation, debugging, optimization, and large-scale experimentation.

• Problem-solving and research skills with the ability to independently drive research/engineering projects.

• Effective communication and collaboration skills for working across research and engineering teams.

• Hands-on experience training or fine-tuning large Vision Language Models or multimodal foundation models at scale.

• Experience with distributed learning frameworks and infrastructure such as PyTorch Distributed, Megatron, Triton, or CUDA.

• Research experience in multimodal reasoning, agentic systems, tool use, OCR, grounding, document understanding, or multimodal retrieval.

• Experience with synthetic data generation, multimodal data curation, or automated evaluation frameworks for VLMs.

• Familiarity with efficient training and inference techniques such as FlashAttention, quantization, tensor parallelism, pipeline parallelism, or memory optimization.

• Experience contributing to open-source ML software and large-scale research codebases.

• Strong publication record in leading AI conferences such as NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, ACL, EMNLP, or related venues.

• Experience collaborating across research, infrastructure, and product-oriented teams to deliver state-of-the-art multimodal systems.