Parallax
Founding Member Of Technical Staff
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About us
Parallax is a new UK-based non-profit research organisation developing open methods and infrastructure for white-box auditing of frontier AI systems. Our mission is to make evidence about models’ internal beliefs, goals, and plans a core component of AI evaluations, allowing evaluators to identify, explain, and predict safety-relevant failures more reliably. We publish our findings, release our methods and infrastructure, and aim to make scientific contributions that remain useful as agentic capabilities of frontier models keep increasing. You can read more about our mission, strategy, and team on our About page.
About the Role
We are recruiting two Members of Technical Staff to join Parallax as founding members of our technical team. As an early member of a fast-moving, highly collaborative team, you will take substantial ownership of projects developing frontier white-box AI auditing technology, from ideation to implementation, evaluation, and release. You will also play a fundamental role in defining Parallax’s character and impact as it scales into a leading European actor in this space.
You will work directly with our co-founders: Mario Giulianelli, our Scientific Director, is an Associate Professor at UCL who was previously a Senior Researcher at the UK AI Security Institute (UK AISI). Gabriele Sarti, our Technical Director, was a postdoctoral researcher at Northeastern University and the National Deep Inference Fabric (NDIF).
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Qualities of a Strong Candidate
- A strong sense of ownership, initiative, and reliability, with an honest desire to make a concrete impact on pressing issues.
- A commitment to research rigour and intellectual honesty, with a tendency for meticulous experimentation, holding themselves to a high bar for final results and write-ups.
- Strong written and verbal communication, low ego, and openness to feedback.
- Ability to learn quickly from teammates and mentors, and mindfully adopt new technologies to accelerate work.
- The ability to move rapidly from scrappy prototyping to careful implementation and robust experimentation, keeping the bigger picture in mind when refining low-level details.
- Deep domain knowledge and research experience in areas such as interpretability, reinforcement learning, and agent evaluations.
- Strong programming ability (in particular Python and PyTorch/HF Transformers ecosystems), with the ability to navigate efficiency and software design trade-offs.
- Experience designing and running large-scale machine learning experiments using multi-GPU setups and making efficient use of inference APIs.
- The ability to identify useful research questions and make progress when the path is unclear or blocked.
- A proven interest in collaborative research, a commitment to openness, and the willingness to contribute across scientific and engineering work.
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A PhD in machine learning or a related field is not required. We welcome applicants who can demonstrate equivalent research ability through other professional routes. If the role interests you but you do not meet every criterion, we still encourage you to apply.
Location, Compensation, and Hiring Process
See the full information relative to this position on our website: https://parallx.ai/careers/founding-member-of-technical-staff
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