O
San Francisco, California, US (On-site)
$295–500K / year
About the Team The Interpretability team studies internal representations of deep learning models.
1 mo. ago
Showing 1–20 of 72 jobs
San Francisco, California, US (On-site)
$295–500K / year
About the Team The Interpretability team studies internal representations of deep learning models.
1 mo. ago
OpenAI
San Francisco, California, US (On-site)
$250–445K / year
About the Team The Alignment team at OpenAI is dedicated to ensuring that our AI systems are safe, trustworthy, and consistently aligned with human…
9 mo. ago
San Francisco, California, US (Hybrid)
$250–445K / year
About the Team The CoT Monitorability team at OpenAI studies whether and when the chain-of-thought of frontier reasoning models is monitorable enough…
4 mo. ago
San Francisco, California, US (On-site)
$350–500K / year
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems.
10 mo. ago
Cartesia
San Francisco, California, US (On-site)
$180–350K / year
About Cartesia Our mission is to architect AI that learns from and interacts with the world like humans do.
9 mo. ago
United States (Remote)
$100–550K / year
Magic’s mission is to build safe AGI that accelerates humanity’s progress on the world’s most important problems.
9 mo. ago
San Francisco, California, US (Hybrid)
$207–335K / year
About the Team Our Safety Systems team is at the forefront of OpenAI's mission to build and deploy safe AGI, driving our commitment to AI safety and…
4 wk. ago
San Francisco, California, US (On-site)
$295–445K / year
About the Team Models are becoming increasingly capable—moving from tools that assist humans to agents that can plan, execute, and adapt in the real world.
2 mo. ago
San Francisco, California, US (Hybrid)
$380–500K / year
About the Team The Agent Safety team works to ensure that increasingly capable AI agents act safely, exercise sound judgment, and remain aligned with…
1 mo. ago
San Francisco, California, US (On-site)
$295–445K / year
About the Team The Safety Systems team is responsible for various safety work to ensure our best models can be safely deployed to the real world to…
9 mo. ago
San Francisco, California, US (On-site)
$295–445K / year
About the team Models are becoming increasingly capable—moving from tools that assist humans to agents that can plan, execute, and adapt in the real world.
2 mo. ago
London, England, GB (On-site)
£260–370K / year
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems.
10 mo. ago
London, England, GB (Hybrid)
$225–290K / year
About Suno We're building the world's first creative entertainment platform, where the entire world can feel the joy and fulfillment of making music.
2 mo. ago
Santa Clara, California, US (On-site)
$232–368K / year
We are now looking for a Principal Thermal Mechanical Photonic Designer.
6 mo. ago
San Francisco, California, US (Hybrid)
$380–500K / year
About the Team The Agent Safety team works to ensure that increasingly capable AI agents act safely, exercise sound judgment, and remain aligned with…
1 mo. ago
San Francisco, California, US (Hybrid)
$295–445K / year
About the Team The RL and Reasoning team drives the core reasoning paradigm and has created groundbreaking innovations such as o1 and o3.
9 mo. ago
Palo Alto, California, US (On-site)
$180–600K / year
SpaceXAI’s mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge.
6 mo. ago
San Francisco, California, US (Hybrid)
$225–318K / year
About the Team Our Robotics team is focused on unlocking general-purpose robotics and pushing towards AGI-level intelligence in dynamic, real-world settings.
1 mo. ago
San Francisco, California, US (Hybrid)
$230–385K / year
About the Team OpenAI’s mission is to ensure that artificial general intelligence (AGI) benefits all of humanity.
9 mo. ago
Santa Clara, California, US (On-site)
$30.00 – $94.00 / hour
We are looking for PhD research interns excited to advance the next generation of large language models through reinforcement learning.
5 mo. ago