Lead AI Engineer

Role Description

Are you ready to be one of the founding members of a new engineering team focused on pioneering creative AI educational resources? You will take ownership of defining, planning, and crafting the overall system architectures for key product areas and driving end-to-end feature development. You will be responsible for developing state-of-the-art algorithms to power the next-generation tools for students and educators. This is a highly collaborative role with the opportunity to evolve in many directions.

• Build and lead a team of AI researchers and engineers
• Deploy, prompt, and fine-tune cutting-edge foundation multimodal models
• Apply foundation models to enhance our curriculum delivery system and product offerings
• Collaborate with cross-functional teams, including product managers, data scientists, and product engineers, to form and solve problems, refine machine learning algorithms, and communicate results
• Regularly run A/B tests, perform analyses, and iterate algorithms based on results
• Work with infrastructure teams on improving the efficiency and stability of machine learning systems
• Develop LMS integrations enabling the use of multiple existing models

Qualifications

• Hands-on experience in one or more of the following areas: Machine Learning, Deep Learning, Recommender Systems, Data Mining, Natural Language Processing, or Computer Vision
• Strong programming skills in Python and/or C/C++, and a deep understanding of data structures and algorithms
• Familiar with architecture and implementation of at least one mainstream machine learning programming framework (TensorFlow/PyTorch/MXNet/etc.)
• Excellent communication, teamwork skills, and a passion for learning new techniques and tackling challenging problems

Requirements

• Prior research/industry experience with deploying, prompting, and fine-tuning foundation models and multimodal models
• Prior research/industry experience using AI/ML to develop psychological profiles
• Prior research/industry experience with applied machine learning, or large-scale recommendation systems
• Publications at major AI-related conferences such as NeurIPS, ICML, ICLR, AAAI, IJCAI, ACL, NAACL, EMNLP, CVPR, ICCV, ECCV, KDD, ICDM, SDM, RecSys, or simply on arXiv but with large impact
• Strong track record in AI-related competitions, or participation in public/open-source AI-related projects of high visibility
• A strong passion for axiomatization and novel systems

Benefits

• Fully Remote
• Equity options
• Health insurance
• Dental insurance
• Paid sick time
• Paid time off
• Parental leave
• Vision insurance
• Family First Culture