Research Engineer

About the role

ABOUT US

FAR.AI http://FAR.AI is a non-profit AI research institute working to ensure advanced AI is safe and beneficial for everyone. Our mission is to facilitate breakthrough AI safety research, advance global understanding of AI risks and solutions, and foster a coordinated global response.

Since our founding in July 2022, we've grown to 50+ staff https://www.far.ai/about/team, published 40+ academic papers https://scholar.google.com/citations?user=FVJ24k8AAAAJ, and convened leading AI safety events https://far.ai/events/. Our work is recognized globally, with publications at premier venues such as NeurIPS, ICML including a Best Paper Honorable Mention in 2026 https://icml.cc/virtual/2026/oral/71065, and ICLR, and features in the Financial Times https://www.ft.com/content/175e5314-a7f7-4741-a786-273219f433a1, Nature News https://www.nature.com/articles/d41586-024-02218-7, Wired Magazine https://www.wired.com/story/jailbreaking-ai-models-google-anthropic-openai-spacexai/ and MIT Technology Review https://www.technologyreview.com/2020/02/28/905615/reinforcement-learning-adversarial-attack-gaming-ai-deepmind-alphazero-selfdriving-cars/. We conduct pre-deployment testing on behalf of frontier developers such as OpenAI, independent evaluations for governments including the EU AI Office https://www.far.ai/news/far-ai-selected-to-lead-eu-ai-act-cbrn-risk-consortium, and publish the AI Security Leaderboard https://leaderboard.far.ai/ based on our red-teaming expertise. We help steer and grow the AI safety field through developing https://arxiv.org/abs/2405.06624 research https://arxiv.org/abs/2506.20702 roadmaps https://www.researchgate.net/publication/396910034_Open_Technical_Problems_in_Open-Weight_AI_Model_Risk_Management with renowned researchers such as Yoshua Bengio; running FAR.Labs https://www.far.ai/programs/far-labs, an AI safety-focused co-working space in Berkeley housing 40+ members; and supporting the community through targeted grants https://www.far.ai/programs/grantmaking to technical researchers.

ABOUT FAR.RESEARCH

We explore promising research directions in AI safety and scale up only those showing a high potential for impact. Once the core research problems are solved, we work to scale them to a minimum viable prototype, demonstrating their validity to AI companies and governments to drive adoption.

We are aiming to rapidly grow our team in the following areas especially, at varying levels of seniority:

- Evals and red-teaming: Conducting pre- and post-release adversarial evaluations of frontier models (e.g. Claude 4 Opus https://x.com/ARGleave/status/1926138376509440433, ChatGPT Agent https://cdn.openai.com/pdf/839e66fc-602c-48bf-81d3-b21eacc3459d/chatgpt_agent_system_card.pdf, GPT-5 https://cdn.openai.com/gpt-5-system-card.pdf); developing novel attacks https://www.far.ai/news/defense-in-depth to support this work; and exploring new threat models (e.g. persuasion https://arxiv.org/abs/2506.02873, tampering risks https://arxiv.org/abs/2507.11630).

- Infrastructure: Maintaining GPU compute infrastructure to support experiments with open-weight models and developing new tooling to allow our research teams to scale their fine-tuning and post-training workflows to frontier open-weight models.