Remote Machine Learning Engineer, Post-Training

Description:

• Cantina is a new social platform founded by Sean Parker, featuring an advanced AI character creator.
• The platform allows users to build, share, and interact with AI bots and friends across the internet.
• Cantina bots are lifelike social creatures that can interact in various online environments.
• The Post-Training team focuses on developing pretrained language models into intelligent and engaging products.
• As a Machine Learning Engineer, Post-Training, you will enhance model performance and training methods, including data, compute, and algorithms.
• Responsibilities include running evaluations of pre-trained models, addressing performance issues, creating datasets, developing algorithms, and contributing to open-source ML projects.

Requirements:

• You must have 5+ years of experience building production-grade LLMs or Speech & Audio machine learning models in industry or academic settings.
• Experience with data processing, analysis, and curation is required.
• A strong understanding of modern machine learning techniques such as DPO, RLHF, and transformers is necessary.
• A track record of exceptional research or creative applied ML projects is essential.
• Experience with product experimentation and A/B testing is required.
• You should have experience training large models in a distributed setting.
• Familiarity with ML deployment and orchestration tools like Kubernetes, Docker, and cloud services is needed.

Benefits:

• Cantina covers 99% of premiums for medical, vision, and dental insurance, along with a One Medical membership.
• Employees receive a monthly stipend of $500 to use as they wish.
• The company offers 15 PTO days per year, 9 sick days, 13 paid company holidays, and an office closure for winter break from Christmas Eve to New Year's Day.
• Employees are eligible to participate in a 401(K) plan from day one of employment.
• Parental leave and fertility support are provided.
• The position offers a competitive salary and equity options.
• In-office employees receive lunch and snacks, while full-time hybrid/remote employees are provided with WFH equipment.