Research Lead – Pre-training Safety

🕒 Setembro 8

🌐 Estados Unidos, Singapura – Remoto

🇺🇸 Estados Unidos – Remoto (EUA) 🇸🇬 Singapura – Remoto

🏄 California – Remoto

🏄 California – Remote

💵 $290.000 - $450.000 / ano

⏰ Tempo Integral

🟠 Sênior

👻 Score fantasma 14%

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FAR.AI

SiteLinkedInTodas as Vagas

11 - 50 funcionários

Fundada em 2022

🤖 Inteligência Artificial

📚 Educação

🤝 Sem Fins Lucrativos

Artificial Intelligence • Education • Non-profit

A Ashby Electrical Limited é uma empreiteira estabelecida em 2018 que se especializa em fornecer soluções elétricas econômicas e sustentáveis para projetos residenciais e comerciais. A empresa se orgulha de entregar trabalho de alta qualidade ao longo do ciclo de vida do projeto, incluindo design, instalação, teste e comissionamento. A Ashby Electrical está comprometida em construir relacionamentos sólidos com seus clientes, fundamentada na confiança, integridade e profissionalismo, garantindo que os projetos sejam concluídos dentro do prazo e do orçamento.

Descrição

• Develop and lead FAR.AI’s pre-training safety research workstream • Direct capability-control research focused on removing harmful capabilities while preserving benign ones • Scale methods such as Deep Ignorance to models with over 100B parameters and over 1T tokens • Partner with the red team to stress-test resulting models and analyze scaling to frontier systems • Research improved data filtering using data attribution, influence-based selection, and sophisticated classifiers • Use gradient routing to isolate dual-use capabilities in model components such as MoE experts • Develop training methods to actively remove harmful capabilities through unlearning and next-token prediction • Add synthetic data to pre-training or mid-training to shape model representations and behavior • Build and lead the team and set its research direction • Mentor Members of Technical Staff and remain hands-on by writing code and running experiments • Articulate a research agenda and theory of change for mitigating catastrophic AI risks or increasing beneficial outcomes • Lead novel research projects with potentially unclear progress or success markers • Share findings through academic publications, blog posts, ML conferences, and policymaker briefings • Contribute to FAR.AI’s intellectual environment and research culture • Build a research field through grantmaking and events • Connect research to real-world deployments through independent testing and government advising

🎯 Requisitos

• Strong existing research track record in AI or another highly technical subject, such as computer science, mathematics, or physics • Deep experience with language-model pretraining, dataset construction, or controlled training experiments • Experience building large-scale pipelines for scoring, filtering, deduplicating, and sampling training corpora • Strong experimental judgment, including safety–capability evaluations, distribution-shift analysis, and statistically rigorous model comparisons • Ability to build and debug research systems directly, from classifier fine-tuning through distributed training and evaluation • Either a clear research agenda with a theory of change, or a strong track record and research space to develop into an agenda • Experience leading a team, mentoring graduate students, or supporting early-career researchers; informal leadership counts • Ability to communicate novel methods and solutions to technical and non-technical audiences • Substantive engagement with machine learning research through prior research, employment, or sustained independent contribution; not a new entrant • Established AI safety publication record preferred • Comfort writing grant proposals and navigating external collaborations preferred • Full-time availability, 40 hours/week • Ability to work remotely in most countries or in person in Berkeley, California or Singapore

🏖️ Benefícios

• Competitive salary of $290,000–$450,000/year depending on experience and location; exceptional candidates may receive a higher salary range • Work-related travel and equipment expenses covered • Catered lunch and dinner at Berkeley offices • Flexible remote or in-person work options • Visa sponsorship for in-person employees • Paid 3–5-day work trial • Sizable compute budgets on a managed cluster • Dedicated engineering team supporting compute infrastructure and experiment scaling • Opportunities to collaborate with governments, leading AI companies, and academics • Professional development through research leadership, mentoring, publications, conferences, grantmaking, and events