TL;DR
Member of Technical Staff - Multimodal Tokenization (AI): Training multimodal tokenizers at web scale for unified interface with multimodal language models with an accent on spatial-temporal compression, world modeling, and cross-modal alignment. Focus on rapidly implementing state-of-the-art deep learning methods and innovating new pretraining ideas and scaling paradigms.
Location: Must be based in the Bay Area [Palo Alto], USA, or be open to relocation to the Bay Area
Salary: $180,000 - $440,000 USD
Company
hirify.global is an AI company focused on creating AI systems to accurately understand the universe and aid humanity in its pursuit of knowledge.
What you will do
- Train multimodal tokenizers at web scale for unified interface with multimodal language models.
- Push boundaries in spatial-temporal compression, world modeling, multimodal reasoning, and cross-modal alignment.
- Rapidly implement the latest state-of-the-art methods from deep learning literature.
- Innovate new ideas for pretraining and new scaling paradigms.
Requirements
- Must be based in the Bay Area [Palo Alto], USA, or be open to relocation to the Bay Area.
- Strong engineering skills with a passion for model-hardware co-design.
- Expertise in ML and large model scaling, familiar with all kinds of scaling laws.
- Familiarity with distributed training, multi-GPU neural network training, and optimizing ML training efficiency.
- Familiarity with state-of-the-art techniques for multimodal tokenizers, especially image, video, and audio.
- Strong communication skills.
- English: B2 required.
Culture & Benefits
- Small, highly motivated team focused on engineering excellence.
- Flat organizational structure where all employees are hands-on and contribute directly.
- Leadership is given to those who show initiative and consistently deliver excellence.
- Comprehensive medical, vision, and dental coverage.
- Access to a 401(k) retirement plan.
- Short & long-term disability insurance and life insurance.
- Various other discounts and perks.
Hiring process
- CV and statement of exceptional work review.
- 15-minute phone interview.
- Four technical interviews (coding assessment, 2-3 technical sessions).
- "Meet the Team" presentation of past exceptional work and vision.
- Goal to finish the main process within one week.
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