Member of Technical Staff - Multi-Modal, Vision

About the Company

Spun out of MIT CSAIL, Liquid AI builds general-purpose AI systems that run efficiently across deployment targets, from data center accelerators to on-device hardware, ensuring low latency, minimal memory usage, privacy, and reliability.

Responsibilities

• Lead new model capabilities end-to-end from task specification through data curation, training recipes, and evaluation
• Improve visual reasoning through reinforcement learning and preference optimization methods
• Push the quality-efficiency frontier on token efficiency via encoder/connector design
• Own major work-streams such as video understanding, preference data quality, or encoder architecture

Requirements

• Hands-on experience in training or evaluating VLMs with demonstrated experimental rigor
• Proficiency in Python and at least one deep learning framework
• M.S. or Ph.D. in Computer Science, Mathematics, or a related field, or equivalent industry experience
• Ability to turn research ideas into scalable implementations

Preferred Qualifications

• Experience building or optimizing multimodal training or data pipelines
• Experience with distributed training (DeepSpeed, FSDP, Megatron-LM, etc.)
• Multimodal post-training experience (SFT, preference optimization, RL-style methods)
• Dataset design and data quality expertise
• Prior open-source contributions on GitHub or Hugging Face
• Published research at top AI conferences (NeurIPS, ICML, CVPR, ECCV, ICLR, ACL, etc.)
• Experience with computer vision or visual representation learning

Benefits

• Competitive base salary with equity
• 100% coverage of medical, dental, and vision premiums for employees and dependents
• 401(k) matching up to 4% of base pay
• Unlimited PTO plus company-wide Refill Days