Research Engineer, Model Performance & Quality

About Anthropic

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.

About the role

As a Research Engineer on the Model Performance team, you will help solve one of our greatest challenges: systematically understanding and monitoring model quality in real-time. This role blends research and engineering responsibilities, requiring you to train production models, develop robust monitoring systems, and create novel evaluation methodologies. 

Representative Projects

• Build comprehensive training observability systems - Design and implement monitoring infrastructure to keep an eye on how model behaviors evolve throughout training.
• Develop next-generation evaluation frameworks - Move beyond traditional benchmarks to create evaluations that capture real-world utility. 
• Create automated quality assessment pipelines - Build custom classifiers to continuously monitor RL transcripts for complex issues
• Bridge research and production - Partner with research teams to translate cutting-edge evaluation techniques into production-ready systems, and work with engineering teams to ensure our monitoring infrastructure scales with increasingly complex training workflows.

You may be a good fit if you:

• Are proficient in Python and have experience building production ML systems
• Have experience with training, evaluating, or monitoring large language models
• Are naturally curious about debugging complex, distributed systems and thinking about failure modes
• Enjoy collaborative problem-solving and working across diverse teams - you’ll work on virtually all stages of our model training pipeline
• Can balance research exploration with engineering rigor.
• Have strong analytical skills for interpreting training metrics and model behavior
• Want to directly impact the quality and safety of deployed AI systems

Strong candidates may have:

• Experience with reinforcement learning and language model training pipelines
• Experience designing and implementing evaluation frameworks or benchmarks
• Background in production monitoring, observability, and incident response
• Experience with statistical analysis and experimental design
• Knowledge of AI safety and alignment research

Strong candidates need not have:

• Formal certifications or education credentials
• Academic research experience or publication history
• Prior experience in AI safety or evaluation specifically

We're looking for thoughtful engineers who are excited about the challenge of measuring and monitoring capabilities we're still discovering. This role offers the opportunity to shape how the field approaches model quality assessment while working on systems that will be critical as AI capabilities continue to advance.

Logistics

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 different

We 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