Research Engineer, Model Evaluations at Anthropic

About AnthropicAnthropics 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 roleAs a Research Engineer on the Model Evaluations team youll lead the design and implementation of Anthropics evaluation platforma critical system that shapes how we understand measure and improve our models capabilities and safety. Youll work at the intersection of research and engineering to develop and implement model evaluations that give us insight into emerging capabilities and build robust evaluation infrastructure that directly influences our training decisions and model development roadmap.Your work will be essential to Anthropics mission of building safe beneficial AI systems. Youll collaborate closely with training teams alignment researchers and safety teams to ensure our models meet the highest standards before deployment. This is a technical leadership role where youll drive both the strategic vision and hands-on implementation of our evaluation systems.ResponsibilitiesDesign novel evaluation methodologies to assess model capabilities across diverse domains including reasoning safety helpfulness and harmlessnessLead the design and architecture of Anthropics evaluation platform ensuring it scales with our rapidly evolving model capabilities and research needsImplement and maintain high-throughput evaluation pipelines that run during production training providing real-time insights to guide training decisionsAnalyze evaluation results to identify patterns failure modes and opportunities for model improvement translating complex findings into actionable insightsPartner with research teams to develop domain-specific evaluations that probe for emerging capabilities and potential risksBuild infrastructure to enable rapid iteration on evaluation design supporting both automated and human-in-the-loop assessment approachesEstablish best practices and standards for evaluation development across the organizationMentor team members and contribute to the growth of evaluation expertise at AnthropicCoordinate evaluation efforts during critical training runs ensuring comprehensive coverage and timely resultsContribute to research publications and external communications about evaluation methodologies and findingsYou may be a good fit if youHave experience designing and implementing evaluation systems for machine learning models particularly large language modelsHave demonstrated technical leadership experience either formally or through leading complex technical projectsAre skilled at both systems engineering and experimental design comfortable building infrastructure while maintaining scientific rigorHave strong programming skills in Python and experience with distributed computing frameworksCan translate between research needs and engineering constraints finding pragmatic solutions to complex problemsAre results-oriented and thrive in fast-paced environments where priorities can shift based on research findingsEnjoy collaborative work and can effectively communicate technical concepts to diverse stakeholdersCare deeply about AI safety and the societal impacts of the systems we buildHave experience with statistical analysis and can draw meaningful conclusions from large-scale experimental dataStrong candidates may also haveExperience with evaluation during model training particularly in production environmentsFamiliarity with safety evaluation frameworks and red teaming methodologiesBackground in psychometrics experimental psychology or other fields focused on measurement and assessmentExperience with reinforcement learning evaluation or multi-agent systemsContributions to open-source evaluation benchmarks or frameworksKnowledge of prompt engineering and its role in evaluation designExperience managing evaluation infrastructure at scale (thousands of experiments)Published research in machine learning evaluation benchmarking or related areasRepresentative projectsDesigning comprehensive evaluation suites that assess models across hundreds of capability dimensionsBuilding real-time evaluation dashboards that surface critical insights during multi-week training runsDeveloping novel evaluation approaches for emerging capabilities like multi-step reasoning or tool useCreating automated systems to detect regression in model performance or safety propertiesImplementing efficient evaluation sampling strategies that balance coverage with computational constraintsCollaborating with external partners to develop industry-standard evaluation benchmarksBuilding infrastructure to support human evaluation at scale including quality control and aggregation systemsThe expectedbase compensation for this position is below. Our total compensation package for full-time employees includes equity benefits and may include incentive compensation.Annual Salary:$300000 - $405000 USDLogisticsEducation requirements: We require at least a Bachelors 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 arent 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 youre interested in this work. We think AI systems like the ones were 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 were 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. Were 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 aboutour policyfor using AI in our application process Key Skills Python,C/C++,Fortran,R,Data Mining,Matlab,Data Modeling,Laboratory Techniques,MongoDB,SAS,Systems Analysis,Dancing Employment Type : Full Time Experience: years Vacancy: 1 Monthly Salary Salary: 300000 - 405000