Liquid AI
Member of Technical Staff - Multi-Modal, Vision
San Francisco · Staff+
Sponsorship not specifiedDetected 273 days ago
PythonAlgorithmsGitDeep LearningComputer VisionResearch
About the role
- We have released four best-in-class models and we're just getting started.
- Success here is measured by the capability of the models we ship.
Responsibilities
- You'll join a focused, hands-on group that works directly on models and collaborates closely with our pretraining, post-training, and infrastructure teams.
- You own your work from architecture to deployment.
- You own a major work-stream (for instance, video understanding, preference data quality, or encoder architecture) end-to-end.
- Full ownership: You own your work from architecture to deployment.
- We partner with enterprises across consumer electronics, automotive, life sciences, and financial services.
Requirements
- Hands-on experience in training or evaluating VLMs with demonstrated experimental rigor.
- Ability to turn research ideas into scalable implementations, refine and iterate through hypotheses.
- Experience with distributed training (DeepSpeed, FSDP, Megatron-LM, etc.).
- 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.
- Building or optimizing multimodal training or data pipelines.
- Multimodal post-training experience (SFT, preference optimization, RL-style methods).
- Dataset design and data quality expertise (quality and diversity assessment, long-tail mining).
- Prior open-source contributions (code, data, models) 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.
- Lead a new model capability end-to-end from task spec through data curation, training recipe, ablations, evaluation, and into the final shipped model.
- Improve visual reasoning through reinforcement learning and preference optimization methods.
Compensation
- Competitive base salary with equity in a unicorn-stage company
- Health: We pay 100% of medical, dental, and vision premiums for employees and dependents
- Financial: 401(k) matching up to 4% of base pay
Benefits
- Compensation: Competitive base salary with equity in a unicorn-stage company
- Health: We pay 100% of medical, dental, and vision premiums for employees and dependents
- Time Off: Unlimited PTO plus company-wide Refill Days throughout the year
- The VLM team builds vision-language models that run on-device, under tight latency and memory constraints, without sacrificing quality.
Company info
- We are scaling rapidly and need exceptional people to help us get there.
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This listing is sourced directly from Liquid AI's careers page and normalized into a canonical job model.