# Research Engineer, Virtual Collaborator (Cowork)

**Company**: Anthropic
**Location**: New York City, NY; San Francisco, CA; Seattle, WA
**Work arrangement**: hybrid
**Experience**: senior
**Job type**: full-time
**Salary**: $500,000 - $850,000 USD
**Category**: Engineering
**Industry**: Technology
**Wikidata**: https://www.wikidata.org/wiki/Q116758847

**Apply**: https://job-boards.greenhouse.io/anthropic/jobs/4946308008
**Canonical**: https://yubhub.co/jobs/job_442b4d5e-4a8

## Description

## 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 organisational 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 visualisation)

- Designing and implementing reinforcement learning pipelines targeted at virtual collaborator use cases (productivity, organisational navigation, vertical domains)

- Building and scaling our data creation platform for generating high-quality, open-ended tasks with domain experts and crowdworkers Integrating real organisational 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 modelling 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.

## 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.

## Your safety matters to us.

To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings.

## 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.

## Skills

### Required
- Python
- Machine learning
- Reinforcement learning
- Data visualisation
- Enterprise tools and APIs

### Nice to have
- Human-in-the-loop training systems
- Crowdsourcing platforms
- Domain expertise in finance, legal, or healthcare workflows