A bit about Cantina:
Cantina, founded by Sean Parker, is a new social platform with the most advanced AI character creator. Build, share, and interact with AI bots and your friends directly in the Cantina or across the internet.
Cantina bots are lifelike, social creatures, capable of interacting wherever humans go on the internet. Recreate yourself using powerful AI, imagine someone new, or choose from thousands of existing characters. Bots are a new media type that offer a way for creators to share infinitely scalable and personalized content experiences combined with seamless group chat across voice, video, and text.
If you're excited about the potential AI has to shape human creativity and social interactions, join us in building the future!
About the role:
We are seeking talented Research Scientists to join our team, focused on advancing the capabilities of our AI-driven social platform. As a Research Scientist, you will play a pivotal role in developing state-of-the-art text models that enable our AI bots to interact in a mult-bot and multi-user environments in real-time.
A bit about the work:
Lead research initiatives to develop large language models (LLMs) optimized for complex conversational scenarios, including multi-turn dialogue, dynamic memory management, and open-ended interactions.
Focus on model efficiency and latency optimization to enable real-time interactions within the product at scale.
Collaborate with product, design and engineering teams to guide research prototypes to production.
Survey and investigate state of the art published research, implement baselines based on that research and extend it given product requirements.
Contribute to the research community through publications and open-source contributions.
A bit about you:
Ph.D. or equivalent experience in Computer Science, Electrical Engineering, or related fields with a focus on natural language processing and generative modeling.
Demonstrated expertise in:
Fine-tuning LLMs with training methodologies, such as RLHF (Reinforcement Learning from Human Feedback), DPO, or contrastive learning.
Evaluation techniques for conversational agents, including challenges related to multi-agent interactions and long-form dialogue.
Optimizing models for deployment using quantization, distillation, or sparse modeling, with experience using tools like vLLMs, DeepSpeed, or Hugging Face Transformers
Proven track record of research excellence demonstrated through publications at top-tier conferences (NeurIPS, ICLR, ACL, EMNLP, AAAI, etc).
Strong programming skills in Python and experience with deep learning frameworks (TensorFlow, PyTorch), along with knowledge of distributed training and inference optimization.
Ability to work independently and collaboratively in a fast-paced, dynamic environment, with a strong sense of ownership and drive to deliver impactful results.
Location:
We have offices located in Sunnyvale, CA, San Francisco, CA and Brooklyn, NY. While we have a strong focus on individuals near our office hubs, we offer fully remote and hybrid employment opportunities.
Pay Equity:
In compliance with Pay Transparency Laws, the base salary range for this role is between $200,000 - $350,000 for those located in the San Francisco Bay Area, New York City and Seattle, WA. When determining compensation, a number of factors will be considered, including skills, experience, job scope, location, and competitive compensation market data.
Application Process: Please submit your resume, cover letter, and any relevant portfolio or publications demonstrating your research contributions in AI.
Benefits Summary:
Health Care — 99% of premiums for medical, vision, dental are fully paid for by Cantina, plus One Medical membership.
Monthly Stipend — $500/month to use on whatever you’d like!
Rest and Recharge — 15 PTO days per year, 10 sick days, all federal holidays, and offices closed for winter break (Christmas Eve to New Years Day)!
401(K) — Eligible to participate on day one of employment.
Parental Leave & Fertility Support
Competitive Salary & Equity
Lunch and snacks provided for in-office employees.
WFH equipment provided for full-time hybrid/remote employees.
Yearly based