Research Scientist

Faculty · UK - Londonmid

En corto

▸Investigar seguridad en IA con enfoque en modelos grandes de lenguaje (LLMs).
▸Diseñar experimentos, escribir código modular en Python/PyTorch y desarrollar herramientas reproducibles.
▸Trabajar con expertos para traducir hallazgos técnicos a instituciones de seguridad y laboratorios de vanguardia.

Excellent communication skills in English

En ~1 minuto te damos: quién te entrevista, las preguntas probables con respuestas desde tu CV, y tu CV adaptado a esta vacante. Gratis, sin tarjeta.

¿Qué piden?

✓Formación sólida en aprendizaje automático y arquitecturas de transformadores (especialmente LLMs).
✓Entendimiento práctico de técnicas de interpretabilidad (blanco y negro), como vectores de control o interpretación mecanicista.
✓Capacidad para formular hipótesis a partir de problemas técnicos estructurados.
✓Habilidades sólidas en Python y PyTorch, con código limpio y modular.
✓Experiencia con Git para control de versiones.
✓Capacidad de comunicación clara para explicar conceptos técnicos complejos.

¿No cumplís todo? Es lo normal — tu dossier gratis te dice qué gaps tenés y cómo cubrirlos en la entrevista.

PythonPyTorchtransformer architecturesLLMswhite-box interpretabilityblack-box interpretabilitysteering vectorsmechanistic interpretabilityGitresearch code

¿A quién escribirle en Faculty?

Tu dossier gratis identifica a las personas que te entrevistarían — con su background, qué valoran y cómo escribirles para destacar antes de aplicar.

Why Faculty? We established Faculty in 2014 because we thought that AI would be the most important technology of our time. Since then, we’ve worked with over 350 global customers to transform their performance through human-centric AI. You can read about our real-world impact here . We don’t chase hype cycles. We innovate, build and deploy responsible AI which moves the needle - and we know a thing or two about doing it well. We bring an unparalleled depth of technical, product and delivery expertise to our clients who span government, finance, retail, energy, life sciences and defence. Our business, and reputation, is growing fast and we’re always on the lookout for individuals who share our intellectual curiosity and desire to build a positive legacy through technology. AI is an epoch-defining technology, join a company where you’ll be empowered to envision its most powerful applications, and to make them happen. About the role As a Research Scientist at Faculty, you will conduct original technical research in AI safety to build the foundation for safe, trustworthy AI deployment. Operating at the forefront of AI, you will design and execute impactful experiments, study model behavior, and develop robust, reproducible tooling. Working alongside Senior and Lead Research Scientists, you will bridge scientific discovery with practical application, helping translate complex technical insights for external partners, frontier labs, and national security institutes. This is an incredible opportunity to hone your expertise, shape emerging safety standards, and solve some of the most critical challenges in modern AI. What you'll be doing: Executing technical research in AI safety by designing and running experiments to study and steer model behavior. Applying white-box and black-box methodologies, focusing on interpretability, steering, and behavioral studies of transformer-based LLMs. Developing high-quality, modular, and reproducible research code in Python using deep learning frameworks like PyTorch. Building and maintaining research infrastructure and technical tooling to accelerate scientific discovery. Documenting and communicating experimental findings through high-quality academic papers, technical reports, and presentations. Collaborating with senior scientists to identify literature gaps, refine hypotheses, and identify research scope. Translating complex technical insights for diverse audiences, including external frontier labs, government bodies, and safety institutes. Who we're looking for: Solid background in machine learning fundamentals and transformer architectures (specifically LLMs). A practical understanding of white-box and black-box interpretability techniques, such as steering vectors or mechanistic interpretability. Demonstrated capability to take structured technical problems and formulate hypotheses Strong programming skills in Python and deep learning frameworks like PyTorch, with a track record of writing clean, modular research code, using Git for version control. Excellent communication , enabling you to translate complex technical concepts and experimental results into clear reports and presentations. Curiosity and analytical rigour , combined with exposure to core AI safety areas such as robustness, evaluations, or uncertainty calibration. Our Recruitment Ethos We aim to grow the best team - not the most similar one. We know that diversity of individuals fosters diversity of thought, and that strengthens our principle of seeking truth. And we know from experience that diverse teams deliver better work, relevant to the world in which we live. We’re united by a deep intellectual curiosity and desire to use our abilities for measurable positive impact. We strongly encourage applications from people of all backgrounds, ethnicities, genders, religions and sexual orientations.

No apliques sin prepararte

Investigamos quién te entrevista, adaptamos tu CV y te ensayamos en vivo — gratis la primera.