Senior Research Engineer

FAR.AI is a non-profit AI research institute dedicated to ensuring advanced AI is safe and beneficial for everyone. The Senior Research Engineer will lead projects focused on AI safety, including detecting deception and preventing catastrophic misuse, while also contributing to high-performance computing initiatives.

Responsibilities:

• 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
• Detecting and preventing deception. Under what conditions can we reliably detect deceptive behaviour from models, and can such behaviour be effectively mitigated at scale? This would focus on large-scale training of transformers
• Preventing catastrophic misuse. Apply our research insights to detect and mitigate vulnerabilities and other risks in frontier AI models. This would focus more on technical leadership
• Accelerating our research. Build frameworks and infrastructure that allows us to ask bigger questions and more rapidly run new experiments, to deepen our research

Requirements:

• 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
• Substantial experience training transformers with common ML frameworks like PyTorch or jax
• Good knowledge of basic linear algebra, calculus, vector probability, and statistics
• 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)
• 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