About the Company
Born from the understanding that AI deployment shouldn't require months of preparation or compromise on quality, we've built a comprehensive platform that turns your brand values into production-ready AI applications in days, not months.
Our product is AI Judges that are trained with proprietary auto-align technology and powered by state-of-the-art research on Alignment and RL. We help companies build AI systems that aren't just safe and reliable, but truly aligned with their brand values and business objectives.
Backed by top-tier Silicon Valley venture capital firms, we're on a mission to make safe, reliable, and highly-performant frontier AI for enterprise use-cases a reality.
Join us in pushing the boundaries of what's possible in AI! Learn more about the company here.
About the Role
As the Engineering Lead, you will play a foundational role in our mission to help enterprises systematically improve their AI applications. You will lead a team of 3-5 high-performing engineers to:
- Pioneer research at the intersection of model evaluation, synthetic data generation, and fine-tuning
- Apply LLM research into development of a comprehensive AI improvement platform
- Collaborate directly with enterprise customers to solve complex AI challenges
- Build scalable systems and infra that deliver enterprise-grade software
- Shape our product roadmap as we expand from assessment capabilities into a comprehensive AI improvement solution
We are operating at the frontier of innovation on AI safety and reliability, and this is your opportunity to make a meaningful impact on establishing new industry standards for AI excellence.
About You
There are a few specific things we will look for that will help you succeed in this role:
- 5-8 years of full-time engineering experience, with 1+ years of engineering/people management
- High agency + bias for action
- Experience with ML in an applied setting, especially with foundation models
- Familiarity with LLM fine-tuning, redteaming, scaling laws, synthetic data, reinforcement learning, reward modeling or automated evaluation. A subset of this works.
- Experience contributing to research communities, including open-source research projects or publishing at top-tier conferences (e.g., CVPR, NeurIPS, ICLR, ICCV/ECCV, BMVC)
Notes
We are working leading global enterprises to deliver cutting-edge AI safety and reliability tools. And we are looking for brilliant, high-agency, low-ego rockstars to join us on this journey. We want the best of the best and firmly believe greatness begets greatness.
Come here to push yourself hard, learn things fast, experience unmatched excellence, and do your life's work.