Principal Applied AI/ML Scientist

Who you are

• 8+ years in ML / applied research roles. A PhD is not required, we value shipping over papers
• You've led multiple 0 to 1 AI or ML projects and shipped practical ML or AI systems
• Strong Python, ML frameworks, and software engineering skills
• You love to learn and are able to do so quickly
• You know how computers work and can apply that to solve hard problems, period
• You constantly strive to hit the right balance between simplicity and flexibility
• You have a talent to grok customer's needs and continuously iterate on your understanding of a problem space based on their feedback, industry trends and available technology
• You are able to work in a team environment, have good communication skills and understand the value of collaboration
• Nice to have: experience working on security related products

What the job involves

• We are looking for a Principal Applied AI Scientist to take product ideas from 0 to 1 and define how we do new AI product innovation
• You'll have a lot of independence: you set the technical direction for AI, and experiment fast with minimal process. With that comes real ownership: you'll be the first AI/ML person in the team, so you'll often be figuring it out without a research org behind you
• This is a hands-on role. Publishing papers and open sourcing results might happen as it helps us and the industry, but is not our main goal
• We have a lot to teach you about security, auth, developer products and many other things. And we also want to learn from you. Join us to have fun learning and collaborating with a great group of people, while having the opportunity to shape a huge industry
• We are looking for someone that both wants to be hands on and think about the industry big picture at the same time:
• Model and solve auth and security related problems using AI/ML, through deep understanding of the inner workings and customer challenges
• Lead end-to-end model development. Apply the right paradigm for the problem, e.g.: training traditional ML models from scratch, or fine-tuning and aligning small/large language models
• Create and maintain evaluation and training datasets and workflows
• Take ideas from research through prototype and product recommendation
• Evaluate outcomes across quality, security, latency, and cost

Benefits

• Work from home opportunities
• Health + Wellness
• Financial Benefits
• Pay + Incentives
• Time Off
• Everyday Living
• Resources