Founding Machine Learning Engineer

Who are we?

GPTZero is the leading platform for detecting AI-generated text. Since launching in January, GPTZero has been used by over 5M people around the world and is depended on by thousands of consumer and enterprise customers. We’ve been covered on the front page of the NYT, BBC, WSJ, WaPo, Fox, NPR, and CNN; and serve >1M unique users per month.

In March, we raised a $3.5M seed round co-led by Uncork Capital and Neo with angel investments by the CEOs of Stability.ai and LatticeHQ, as well as the former CEOs of NYT and Reuters. We’re solving novel, challenging problems in NLP and ML, and deploying cutting-edge solutions to detect the origin and veracity of the information on the web.

We’ve built a team from Meta, Uber, Microsoft, and Robinhood, as well as AI research labs from Princeton, Vector, MILA, and Caltech. To continue our rapid growth, we're looking for people who are passionate about this mission to join us!

What we're looking for

In this role, you’ll build machine learning models that power AI-detection and verification at GPTZero. You’ll engage in the entire life cycle, from research, data, training, evaluation, and deployment. You’ll be building cutting-edge models with a global reach for over 1M users.

Responsibilities

• Design, train, and fine-tune state-of-the-art large language models

• Build efficient and scalable ML training and inference systems

• Build pipelines to generate synthetic datasets of AI text and ingest datasets of human text

• Design prompts to adversarially attack our models

• Research the literature for state-of-the-art methods and models to solve novel problems

• Work closely with product teams to develop intuitive applications

Qualifications

• Proficiency in Python and PyTorch

• Past experience with applied NLP models (i.e. Transformer models)

• Ability to scope, plan, and execute projects independently

• Strong collaboration and communication skills

• Wear multiple hats and be a leader as our team grows

• Work with 5 hours of overlap with Eastern Standard Time

• Bonus: experience with distributed training

• Bonus: experience with classic NLP (NER, POS tagging)

• Bonus: publications at top-tier ML venues

• Bonus: Understanding of how machine learning models fail in the wild

Our Perks

• 🏥 Health, dental, and mental health benefits

• 💻 Remote work with co-working hubs in Toronto and NYC

• 🚀 Competitive salary and equity

• 🏝 Generous PTO and holidays

• 🎉 Regular company retreats

• 🙌 Wellness and learning stipend