Senior Research Engineer

Senior Research Engineer

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 40+ staff, published 40+ academic papers, and convened leading AI safety events. Our work is recognized globally, with publications at premier venues such as NeurIPS, ICML, and ICLR, and features in the Financial Times, Nature News and MIT Technology Review. We conduct pre-deployment testing on behalf of frontier developers such as OpenAI and independent evaluations for governments including the EU AI Office.

We help steer and grow the AI safety field through developing research roadmaps with renowned researchers such as Yoshua Bengio; running FAR.Labs, an AI safety-focused co-working space in Berkeley housing 40 members; and supporting the community through targeted grants to technical researchers.

We are aiming to rapidly grow our team in the following areas:

• Mitigating AI deception:
  Studying when lie detectors induce honesty or evasion, and developing for deception and sandbagging
• Evals and red-teaming:
  Conducting pre- and post-release adversarial evaluations of frontier models (e.g. Claude 4 Opus, ChatGPT Agent, GPT-5); developing novel attacks to support this work; and exploring new threat models (e.g. persuasion, tampering risks).
• 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.
• Adversarial Robustness:
  Working to rigorously solve these security problems through building a science of security and robustness for AI, from demonstrating superhuman systems can be vulnerable, to scaling laws for robustness and jail breaking constitutional classifiers
• Mechanistic Interpretability:
  Finding issues with Sparse Autoencoders, probing deception using Among Us, understanding learned planning in Soko Ban and interpretable data attribution.

FAR.AI is one of the largest independent AI safety research institutes, and is rapidly growing with the goal of diversifying and deepening our research portfolio. We would welcome the opportunity to add new research directions if you are a senior researcher with a strong vision and would like to pitch us on it.

This role would be a good fit for an experienced machine learning engineer, or an experienced software engineer looking to transition to AI safety research. All candidates are expected to:

• Have significant software engineering experience. Evidence of this may include prior work experience and open-source contributions.
• Be fluent working in Python.
• Be results-oriented and motivated by impactful research.
• Bring prior experience mentoring other engineers or scientists in engineering skills.

Additionally, candidates are expected to bring expertise in one of the following areas corresponding to the core competencies our different research teams most need:

• Option 1 – Machine Learning:
  Substantial experience training transformers with common ML frameworks like PyTorch or jax. Good knowledge of basic linear algebra, calculus, vector probability, and statistics.
• Option 2 – High-Performance Computing:
  Power user of cluster orchestrators such as Kubernetes (preferred) or SLURM. Experience building high-performance distributed-systems (e.g. multi-node training, large-scale numerical computation). Experience optimizing and profiling code (ideally including on GPU, e.g. CUDA kernels).
• Option 3 – Technical Leadership:
  Experience designing large-scale software systems, whether as an architect in greenfield software development or leading a major refactor. Comfortable project managing small teams, such as chairing stand-ups and developing detailed roadmaps to execute on a 3-6 month research vision.

As a Member of Technical Staff (Senior Research Engineer) you would join one of our existing work streams and lead projects there:

• Detecting and preventing deception.…