• A game for fun, a laboratory for safety,
    and a sandbox for culture.
    All one platform.

Encultured AI is a video game company focused on enabling the safe introduction of AI technologies into our game world.

Team

Leadership

Photo of Andrew Critch
Dr. Andrew Critch
CEO & Co-founder

Andrew is deeply driven to contribute to AI safety efforts on a global scale. Immediately prior to Encultured, Andrew spent 5 years working as a full-time research scientist at UC Berkeley, within the Center for Human-Compatible AI (CHAI), where he retains a part-time appointment. In 2017, Andrew also co-founded the Berkeley Existential Risk Initiative, a non-profit dedicated to improving humanity’s long-term prospects for survival and flourishing, where he volunteered as Executive Director for three years, and now volunteers as President. Andrew also established the Survival and Flourishing Fund and Survival and Flourishing Projects with the support of philanthropist Jaan Tallinn, and co-developed the S-process for philanthropic grant-making with Oliver Habryka.

In 2013, Andrew earned his Ph.D. in mathematics at UC Berkeley studying applications of algebraic geometry to machine learning models. During that time, he cofounded the Center for Applied Rationality (CFAR) and the Summer Program on Applied Rationality and Cognition (SPARC). He was offered university faculty and research positions in mathematics, mathematical biosciences, and philosophy, worked as an algorithmic stock trader at Jane Street Capital’s New York City office (2014-2015), and as a Research Fellow at the Machine Intelligence Research Institute (2015-2017).

Most recently, Andrew had the good sense to be super-impressed by Nick’s amazing engineering skills and realized they should found a company together :)

icon-email
critch@encultured.ai

Photo of Nick Hay
Dr. Nick Hay
CTO & Co-founder

Nick wants to ensure that powerful AI is developed for the benefit of humanity, and believes that to do this we need a good understanding not only of artificial intelligence but also of human intelligence, including deep questions about human minds and culture spanning anthropology, cognitive linguistics, and neuroscience. Prior to Encultured, Nick spent 5 years at Vicarious AI working on approaches to artificial general intelligence (AGI) grounded in real-world robotics. In 2015, Nick earned his PhD at UC Berkeley under Professor Stuart Russell applying reinforcement learning and Bayesian analysis to the metalevel control problem: how can an agent learn to control its own computations.

Nick first began thinking deeply about the impact of AI on humanity upon reading Eliezer Yudkowsky’s Creating Friendly AI in 2001, subsequently interning at MIRI in 2006 and attending the Singularity Summit in 2007. Originally hailing from New Zealand, Nick is still getting used to walking upside down.

icon-email
nick@encultured.ai

Photo of Brandon Reinhart
Brandon Reinhart
Game Director

Brandon has been a professional game developer since 1998, starting his career at Epic Games with engineering and design on Unreal Tournament and Unreal Engine 1.0. More recently, Brandon spent 12 years at Valve wearing (and inventing) hats. Many, many hats… Brandon has spent considerable amounts of time in development and leadership on Team Fortress 2 and Dota 2 where he wrote mountains of code and pioneered modern approaches to game development. Also an advisor for the Makers Fund family of companies, Brandon offers his expertise to game startups at all stages of growth.

Brandon’s interest in AI risk began in 2002 with his exposure to the SL4 mailing list and the extropian community and later his attendance at the prototype CFAR camp in 2011. Brandon is excited to turn that interest into impact.

icon-email
brandon@encultured.ai

What kind of game are we building?

It's a surprise 😉

Job Openings

Join our team and help define it! We are always looking for collaborators and visionaries excited to experiment. Our current openings:


The following positions have been filled, but please check back — we are always on the lookout for new team members!

  • Game Developer - Rust Game Engineer
  • Game Developer - Gameplay Network Engineer
  • Game Developer - Graphics Engineer
Job: ML Engineer - LLM Specialist

Machine Learning Engineer - LLM Specialist

Location

Mostly remote, over Zoom calls and Discord. At least once per week we work together in person in the San Francisco / Berkeley area for an in-person workday, so if you live nearby it’d be great to have you attend those.

Compensation

Starting between $120k and $180k per year depending on experience, plus healthcare benefits, and equity incentives vesting over 5 years, with raises also becoming available with good individual performance or team-wide accomplishments that expand our revenue stream. We also offer a Safe-Harbor 401(k) with the IRS maximum employer matching.

Qualifications

In this role we need candidates to have experience with building and training large language models (LLMs).

In addition, we have two tiers of qualification for this role: Junior ML Engineer and Senior ML Engineer. To qualify directly for the Senior title upon joining, we require candidates who have received a Bachelor’s degree or above in computer science, physics, mathematics, or a closely related field.

These are not required, but our team will welcome and make good use of experience with:
  • building and training reinforcement learning algorithms and/or environments,
  • applying and developing AI alignment methods,
  • research on humans and human culture, including but not limited to background in the humanities, social sciences, cognitive science, and biology,
  • machine learning interpretability research and tools,
  • PhD-level research and writing.
Apply for this ML Engineer position
Job: ML Engineer - RL Specialist

Machine Learning Engineer - RL Specialist

Location

Mostly remote, over Zoom calls and Discord. At least once per week we work together in person in the San Francisco / Berkeley area for an in-person workday, so if you live nearby it’d be great to have you attend those.

Compensation

Starting between $120k and $180k per year depending on experience, plus healthcare benefits, and equity incentives vesting over 5 years, with raises also becoming available with good individual performance or team-wide accomplishments that expand our revenue stream. We also offer a Safe-Harbor 401(k) with the IRS maximum employer matching.

Qualifications

In this role we need candidates to have experience with building and training reinforcement learning algorithms and/or environments.

In addition, we have two tiers of qualification for this role: Junior ML Engineer and Senior ML Engineer. To qualify directly for the Senior title upon joining, we require candidates who have received a Bachelor’s degree or above in computer science, physics, mathematics, or a closely related field.

These are not required, but our team will welcome and make good use of experience with:
  • building and training large language models (LLMs),
  • applying and developing AI alignment methods,
  • research on humans and human culture, including but not limited to background in the humanities, social sciences, cognitive science, and biology,
  • machine learning interpretability research and tools,
  • PhD-level research and writing.
Apply for this ML Engineer position
Job: ML Engineer - Reward-Modeling Specialist

Machine Learning Engineer - Reward-modeling Specialist

Location

Mostly remote, over Zoom calls and Discord. At least once per week we work together in person in the San Francisco / Berkeley area for an in-person workday, so if you live nearby it’d be great to have you attend those.

Compensation

Starting between $120k and $180k per year depending on experience, plus healthcare benefits, and equity incentives vesting over 5 years, with raises also becoming available with good individual performance or team-wide accomplishments that expand our revenue stream. We also offer a Safe-Harbor 401(k) with the IRS maximum employer matching.

Qualifications

In this role we need candidates to have experience with applying and developing algorithms that learn to model human preferences represented as reward functions.

In addition, we have two tiers of qualification for this role: Junior ML Engineer and Senior ML Engineer. To qualify directly for the Senior title upon joining, we require candidates who have received a Bachelor’s degree or above in computer science, physics, mathematics, or a closely related field.

These are not required, but our team will welcome and make good use of experience with:
  • building and training reinforcement learning algorithms and/or environments,
  • building and training large language models (LLMs),
  • applying and developing AI alignment methods,
  • research on humans and human culture, including but not limited to background in the humanities, social sciences, cognitive science, and biology,
  • machine learning interpretability research and tools,
  • PhD-level research and writing.
Apply for this ML Engineer position

Contact Us

Questions? Let’s talk!