FAR AI is seeking applications for an Engineering Manager to lead our engineering team and help build our broader technical team executing on AI safety research projects.
FAR AI is a technical AI research non-profit, focused on ensuring the safe development and deployment of frontier AI technologies.
Since starting in July 2022, FAR has grown to 12 FTE, produced 13 academic papers, hosted events for some of the world’s leading AI & computer science researchers, and opened our AI safety focused co-working space which is home to around 40 members.
About FAR Research
Our research team likes to move fast. We explore promising research directions in AI safety and scale up only those showing a high potential for impact. Unlike other AI safety labs that take a bet on a single research direction, FAR aims to pursue a diverse portfolio of projects. We also put our research into practice through red-teaming engagements with frontier AI developers.
Our current focus areas are building a science of robustness (e.g. finding vulnerabilities in superhuman Go AIs), finding more effective approaches to value alignment (e.g. training from language feedback), and model evaluation (e.g. inverse scaling and codebook features).
Other FAR Projects
To build a flourishing field of AI safety research, we host targeted workshops and events, and operate a co-working space in Berkeley, called FAR Labs. Our previous events include the International Dialogue for AI Safety that brought together prominent scientists (including 2 Turing Award winners) from around the globe, culminating in a public statement calling for global action on AI safety research and governance. We recently hosted the New Orleans Alignment Workshop for over 140 researchers from academia and industry to learn about AI safety and find collaborators. For more information on FAR AI’s activities, please visit our latest post.
About the Role
As (the first) Engineering Manager at FAR, you will play a crucial role to build and oversee a team of Research Engineers, who are working to ensure the safe and responsible development of advanced artificial intelligence systems.
- Team Leadership and Management. Lead and grow our team of Research Engineers from 3 to 6 FTE.
- Strategy. Contribute to the strategic planning of research projects, ensuring alignment with FAR’s goals and objectives.
- Project Management. Oversee the project lifecycle from start to finish, working closely with all members of our research teams (Advisors, Engineers, Scientists) inside and outside of FAR.
- Innovation. Run scientific experiments and contribute to the development of scalable implementations of machine learning algorithms. You will be credited as an author in submissions to peer reviewed venues (e.g. NeurIPS, ICLR, JMLR).
- Flexibility and Variety. Focus on engineering execution but contribute to all aspects of the research project. We expect everyone on the project to help shape the research direction, analyze experimental results, and participate in the write-up of results.
- Collaboration and Networking. Foster strong relationships with collaborators from various academic labs and research institutions, facilitating the exchange of ideas and methodologies.
- Talent Development. Nurture the professional growth of your team and collaborators through regular project meetings, mentorship, and constructive feedback.
- Learning and Development. Pursue continual development of your skills through internal and external resources. You will have an opportunity in the role to develop your research taste and high-level views on AI safety research by collaborating with our Research Scientists. We are excited to support our team to grow in other areas, and will have a dedicated Learning & Development budget.
You should be excited to help make AI systems safe. You are expected to have a minimum of 2 years experience leading technical projects or teams, within software engineering or machine learning domains.
It is essential that you have a:
- Track record of leading or managing technical projects or teams, ideally in a startup or research environment
- Strong foundation in software engineering, with proficiency in at least one object-oriented programming language (preferably Python).
- Are results-oriented and motivated by impactful research.
- Excellent ability to communicate complex technical concepts and lead collaborative efforts.
It is preferable that you have:
- Experience with machine learning methodologies and frameworks like PyTorch or TensorFlow.
- Familiarity with Operating system internals and distributed systems.
- Familiarity with basic linear algebra, calculus, vector probability, and statistics.
- Publications or open-source software contributions.
About the Projects
As Engineering Manager you would lead collaborations and contribute to many projects, with examples below:
- Scaling laws for prompt injections. Will advances in capabilities from increasing model and data scale help resolve prompt injections or “jailbreaks” in language models, or is progress in average-case performance orthogonal to worst-case robustness?
- Robustness of advanced AI systems. Explore adversarial training, architectural improvements and other changes to deep learning systems to improve their robustness. We are exploring this both in zero-sum board games and language models.
- Mechanistic interpretability for mesa-optimization. Develop techniques to identify internal planning in models to effectively audit the “goals” of models in addition to their external behavior.
- Redteaming of frontier models. Apply our research insights to test for vulnerabilities and limitations of frontier AI models prior to deployment.
You will be an employee of FAR AI, a 501(c)(3) research non-profit.
- Location: Both remote and in-person (Berkeley, CA) are possible. We sponsor visas for in-person employees, and can also hire remotely in most countries.
- Hours: Full-time (40 hours/week).
- Compensation: $125,000-$250,000/year* depending on experience and location. We will also pay for work-related travel and equipment expenses. We offer catered lunch and dinner at our offices in Berkeley. *For exceptional candidates with an outstanding track record we may be able to offer additional compensation.
- Application process: A 90-minute programming assessment, 2 1-hour interviews, and a 1-2 week paid work trial. If you are not available for a work trial we may be able to find alternative ways of testing your fit.