Anthropic· AI Research & Engineering· New York City, NY; San Francisco, CA; Seattle, WA
Research Engineer, Virtual Collaborator (Cowork)
Classified Tasks (11)
Automate 0%Augment 82%Human-Only 18%
Augment (9)
AI assists, human decides
Design and implement reinforcement learning environments for virtual collaborator workflows
technical
Train Claude on document manipulation tasks focused on understanding document content
technical
Train Claude on enhancing documents (e.g., formatting, editing) with good taste
creative
Train Claude on co-creating documents across Office formats and data visualizations
technical
Design and implement reinforcement learning pipelines targeted at productivity, organizational navigation, and vertical-domain use cases
technical
Build and scale the data creation platform for generating high-quality, open-ended tasks
technical
Integrate real organizational data to create realistic training environments
technical
Develop robust evaluation systems that maintain quality while preventing reward hacking
analytical
Train Claude on realistic tasks ranging from navigating internal knowledge to creating financial models
technical
Human-Only (2)
Requires human judgment
Collaborate with domain experts and crowdworkers to generate high-quality, open-ended tasks
communication
Partner directly with product teams (e.g., Cowork, claude.ai) to ensure training aligns with product features
leadership
Job description
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 We are looking for a Research Engineer to help us train Claude specifically for virtual collaborator workflows. While Claude excels at general tasks, a lot of knowledge work requires targeted training on real organizational data and workflows. Your job will be to design and implement reinforcement learning (RL) environments that transform Claude into the best virtual collaborator, training on realistic tasks from navigating internal knowledge to creating financial models. Responsibilities: Training Claude on document manipulation with good taste, including understanding, enhancing, and co-creating (e.g., Office doc formats, data visualization) Designing and implementing reinforcement learning pipelines targeted at virtual collaborator use cases (productivity, organizational navigation, vertical domains) Building and scaling our data creation platform for generating high-quality, open-ended tasks with domain experts and crowdworkers Integrating real organizational data to create realistic training environments Developing robust evaluation systems that maintain quality while avoiding reward hacking Partnering directly with product teams (e.g., Cowork, claude.ai) to ensure training aligns with product features You may be a good fit if you: Are a very experienced Python programmer who can quickly produce reliable, high quality code that your teammates love using Have 5-8 years of strong machine learning experience Thrive at the intersection of research and product, with a pragmatic approach to solving real-world problems Are comfortable with ambiguity and can balance research rigor with shipping deadlines Enjoy collaborating across multiple teams (data operations, model training, product) Can context-switch between research problems and product engineering tasks Care about making AI genuinely helpful for everyday enterprise workflows Strong candidates may also have experience with: Creating RL envs for realistic tasks. Reward modeling and preventing reward hacking Building human-in-the-loop training systems or crowdsourcing platforms Working with enterprise tools and APIs (Google Workspace, Microsoft Office, Slack, etc.) Developing evaluation frameworks for open-ended tasks Domain expertise in finance, legal, or healthcare workflows Creating scalable data pipelines with quality control mechanisms Translating product requirements into technical training objectives Deadline to apply: None. Applications will be reviewed on a rolling basis. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $500,000 — $850,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant t