Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.
When you look at the responses from today's leading language models, do you wonder, "How do we align these systems with human values and preferences?" or “How can we improve an LLM’s abilities beyond what a human can achieve?”
The Reward Modeling team at Anthropic is working to develop sophisticated techniques for teaching AI systems to understand and embody human values, as well as to push forward AI capabilities. We believe that robust reward models are critical to training AI systems that advance the frontier of safety and capabilities. We're looking for engineers to join our efforts to push forward the science of reward modeling
Note: For this role, we conduct all interviews in Python. We have filled our headcount for 2025. However, we are leaving this form open as an expression of interest since we expect to be growing the team in the future, and we will review your application when we do. As such, you may not hear back on your application to this team until the new year
Responsibilities:- Help implement novel reward modeling architectures and techniques
- Optimize training pipelines
- Build and optimize data pipelines
- Collaborate across teams to integrate reward modeling advances into production systems
- Communicate engineering progress through internal documentation and potential publications
- Have a strong engineering background in machine learning, with demonstrable expertise in preference learning, reinforcement learning, deep learning, or related areas
- Are proficient in Python, deep learning frameworks, and distributed computing
- Are familiar with modern LLM architectures and alignment techniques
- Have experience with improving model training pipelines and building data pipelines
- Are comfortable with the experimental nature of frontier AI research
- View research and engineering as complementary disciplines and are willing to implement some research ideas
- Can clearly communicate complex technical concepts and research findings
- Have a deep interest in AI alignment and safety
- Proficiency in Python and experience with deep learning frameworks is required for this role
Experience with reward models is not required, but experience with LLMs or other large models is a significant plus. We welcome candidates at various experience levels, with a preference for senior engineers who have hands-on experience with frontier AI systems.
The expected base compensation for this position is below. Our total compensation package for full-time employees includes equity, benefits, and may include incentive compensation.
Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience.
Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.
How we're differentWe believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.
The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process
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What We Do
Anthropic is an AI safety and research company that’s working to build reliable, interpretable, and steerable AI systems. Our research interests span multiple areas including natural language, human feedback, scaling laws, reinforcement learning, code generation, and interpretability.
