Research Scientist - Vision Language Model

Key Responsibilities

Research and development of next-generation Vision Language Models across pre-training, instruction tuning, reasoning, and agents.

Develop novel architectures and training methodologies for integrating visual understanding, language reasoning, and tool-use capabilities.

Research efficient multimodal learning techniques, including data-efficient training, long-context modeling, model modularity, and inference optimization.

Build and improve large-scale multimodal datasets, synthetic data generation pipelines, and evaluation benchmarks for VLM capabilities.

Investigate multimodal reasoning, agentic behavior, OCR, grounding, document understanding, chart understanding, and visual question answering capabilities.

Contribute to technical reports, research publications, and open-source software.

Represent MBZUAI at research conferences and industry events, showcasing advancements in multimodal foundation models and large-scale AI systems.

Mentor junior researchers and collaborate across teams to drive impactful research initiatives.

Academic Qualifications

PhD or equivalent research experience in Machine Learning, Computer Vision, Natural Language Processing, or Multimodal AI.

Preferred Skills

• 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.

Compensation

$150,000 – $450,000/year + discretionary performance bonus + benefits

The posted salary range represents the company’s good faith estimate of the base compensation for this position upon hire. The actual base compensation offered may vary within this range depending on individual qualifications, including but not limited to relevant skills, experience, education, certifications, and specific business needs. In addition to base salary, total compensation includes an annual discretionary performance bonus and comprehensive benefits.

Benefits Include

• Comprehensive medical, dental, and vision benefits
• Bonus
• 401K Plan
• Generous paid time off, sick leave and holidays
• Paid Parental Leave
• Employee Assistance Program
• Life insurance and disability