Scientist Jobs in Berkeley, CA

About Us

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 , published , and convened leading . Our work is recognized globally, with publications at premier venues such as NeurIPS, ICML including a , and ICLR, and features in the , , and . We conduct pre-deployment testing on behalf of frontier developers such as OpenAI, independent evaluations for governments , and publish the based on our red-teaming expertise. We help steer and grow the AI safety field through with renowned researchers such as Yoshua Bengio; running , an AI safety-focused co-working space in Berkeley housing 40+ members; and supporting the community through 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. , , ); developing to support this work; and exploring new threat models (e.g. , ).

• 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.

We are also seeking more senior candidates in the following research areas:

• Mitigating AI deception: Studying when , and developing model organisms for deception and sandbagging

• Adversarial Robustness: Working to rigorously solve these security problems through building a science of security and robustness for AI, from , to and

• Mechanistic Interpretability: F Sparse Autoencoders, probing deception using , understanding in SokoBan and interpretable data attribution.

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.

About the Role

We organize our team as Members of Technical Staff, with significant overlap between scientist and engineer roles. As a scientist, you will take ownership of and accelerate existing AI alignment research agendas. You can publish research findings broadly and engage with the AI alignment community. If you are an experienced research scientist, then we would be excited to incubate your agenda at FAR using our existing infrastructure and world-class team.

You will receive engineering mentorship via code review, pair programming and regular 1-to-1s. Alongside the engineers, you will be involved in develop scalable implementations of machine learning algorithms and using them to run scientific experiments,

You are encouraged to develop your research taste, proposing novel directions and joining a research pod which suits your interests. You are welcome to take time to study and to attend conferences free of charge. Our technical team is organized into research pods to enable continuity of organizational structure whilst each pod can pivot through varied research projects.

Beyond , you can work with national AI safety institutes, frontier model developers and top academics.

About You

We are excited by unconventional backgrounds. You may have the following:

• New and under-explored AI alignment idea(s).

• Experience leading and/or playing a senior role in research projects related to machine learning.

• Ability to effectively communicate novel methods and solutions to both technical and non-technical audiences.

• PhD or several years research experience in computer science, artificial intelligence, machine learning or statistics.

Benefits*

• Health Insurance - 94% of Insurance premium paid by Organization commencing within 1 month after your start date

• Retirement - 401(k) plan with up to 2% match

• PTO - 25 days Paid Time Off per year, accrued weekly and up to 10 days of paid sick leave per year

• Paid Leave - Paid Bereavement, Family, Medical and Pregnancy Disability Leave

• WFH Stipend & Equipment- Work computer and stipend provided for eligible employees

• Catered Meals (Berkeley Office Only) - Catered lunches and dinners on workdays at our office

*(Available only to full-time employees located in the US)

Logistics

If based in the USA or Singapore, you will be an employee of (501(c)(3) research non-profit / non-profit CLG). Outside the USA or Singapore, you will be employed via an EOR organisation on behalf of or as a contractor.

• Location: Both remote and in-person (Berkeley, CA or Singapore) are possible. We sponsor visas for in-person employees, and can hire remotely in most countries.

• Hours: Full-time (40 hours/week).

• Compensation: $150,000 to $250,000 per year. Compensation is determined by our salary bands and your level of experience, with adjustments for location. We also pay for work-related travel and equipment expenses, and offer catered lunch and dinner at our office in Berkeley.

• Application process: A 72-minute programming assessment, two interviews with members of our technical staff, and a paid work trial lasting up to 1 week. If you are not available for a work trial we may be able to find alternative ways of testing your fit.

If you have any questions about the role, feel free to contact us at . Otherwise, if you don't have questions, the best way to ensure a proper review of your skills and qualifications is by applying directly via the application form. Please don't email us to share your resume (it won't have any impact on our decision). Thank you!