is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. At Anthropic, we believe the most impactful safety research will require access to frontier AI systems. The most powerful AIs will operate not just on text but also other modes of data, including images, video and audio. Such … these risks. Our team works across many parts of a large stack that includes training, inference, system design and data collection. Some of our core focus areas are: Foundational Research We develop new architectures for modeling multimodal data and study how they interact with text-only models at scale. Building Infrastructure We work on many infrastructure projects including: Complex … towards flexibility and impact Pick up slack, even if it goes outside your job description Enjoy pair programming (we love to pair!) Want to learn more about machine learning research Care about the societal impacts of your work Strong candidates may also have experience with: High performance, large-scale ML systems GPUs, Kubernetes, Pytorch, or OS internals Language modeling More ❯
helpful, honest, and harmless, and are interested in the ways that this could be challenging in the context of human-level capabilities. You could describe yourself as both a scientist and an engineer. As a Research Engineer on Alignment Science, you'll contribute to exploratory experimental research on AI safety, with a focus on risks from powerful … provides an overview of topics that the Alignment Science team is either currently exploring or has previously explored. For the London team, we are opportunistically hiring for the following research areas: AI Control: Creating methods to ensure advanced AI systems remain safe and harmless in unfamiliar or adversarial scenarios. Alignment Stress-testing : Creating model organisms of misalignment to improve … of novel LLM-generated jailbreaks. Write scripts and prompts to efficiently produce evaluation questions to test models' reasoning abilities in safety-relevant contexts. Contribute ideas, figures, and writing to research papers, blog posts, and talks. Run experiments that feed into key AI safety efforts at Anthropic, like the design and implementation of our Responsible Scaling Policy. You may be More ❯
The Science of Evaluations Team AISI's Science of Evaluations team will conduct applied and foundational research focused on two areas at the core of our mission: (i) measuring existing frontier AI system capabilities and (ii) predicting the capabilities of a system before running an evaluation. Measurement of Capabilities: The goal is to develop and apply rigorous scientific techniques … for the measurement of frontier AI system capabilities, so they are accurate, robust, and useful in decision making. This is a nascent area of research which supports one of AISI's core products: conducting tests of frontier AI systems and feeding back results, insights, and recommendations to model developers and policy makers. The team will be an independent voice … we would be able to do this at some point early in the training process of a new model, using information about the architecture, dataset, or training compute. This research aims to provide us with advance warning of models reaching a particular level of capability, where additional safety mitigations may need to be put in place. This work is More ❯
San Francisco, California, United States Hybrid / WFH Options
OpenAI
About the Team The Future of Computing is an Applied Research team focused on prototyping and exploring how (consumer) computing might holistically evolve as we advance on our mission of building AGI. About the Role As a Research Engineer on the Future of Computing team, you will work together with both the best research scientists in the … world and the greatest design talent of our generation to push the frontier of model capabilities. The ideal candidate will have a research background and experience shipping AI products that involve novel sensor inputs (think IMU data or other time-series data). This role is based in San Francisco, CA. We use a hybrid work model of … employees. In this role you will: Train and evaluate multimodal SoTA models along axis that are important to our emerging explorations. Run through the necessary walls to take nascent research capabilities and turn them into capabilities we can build on top of. You might thrive in this role if you: Love exposure to a bit of everything - we're More ❯
