AI Research Engineer (Multi-Modal & Vision)

About the role

As a member of the AI model team, you will drive innovation in training and optimizing vision-language models with a focus on real-world deployment. Your work will span the full model development lifecycle - from data curation and training pipeline design to model evaluation and optimization - with the goal of building models that are both highly capable and practical to deploy at scale.

What you'll do

• Conduct end-to-end research and engineering on vision-language models, covering training, evaluation, and optimization across the full model development lifecycle
• Design and implement post-training pipelines including supervised fine-tuning, knowledge distillation, and reinforcement learning from human feedback
• Develop and maintain high-quality multimodal datasets, including data curation, filtering, and balancing for domain-specific tasks
• Drive model efficiency and deployability, adapting models for resource-constrained environments using compression and optimization techniques
• Design and implement evaluation frameworks and benchmarks to measure model performance, robustness, and real-world task success

What you need

• Research
• Git
• Lean
• M.Sc or PhD or B.Tech or B.E. or B.Sc or BCA

Good to have

• Machine learning