Data Operations Manager
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
Anthropic is seeking a Data Operations Manager to join our growing Human Data Operations team. In this role, you'll work across multiple research teams to scope, execute, and manage a portfolio of human data projects that directly contribute to improving our AI models. You'll be responsible for efficiently collecting high-quality human feedback data that helps our researchers build more capable, safer, and more helpful AI systems.
As a Data Operations Manager, you'll serve as a key interface between research teams and our human data collection resources, ensuring our projects are executed with speed, quality, and efficiency.
At Anthropic, we believe that AI systems should be safe, beneficial, and aligned with human values. As a Human Data Operations Associate, you'll play a critical role in developing the human feedback data that helps shape these systems. If you're passionate about AI safety and excited to contribute to cutting-edge research while solving complex operational challenges, we'd love to hear from you.
Responsibilities
- Project Management: Manage end-to-end human data collection projects across multiple research teams, from scoping and planning to execution and quality control
- Operations Support: Work closely with researchers to understand their data needs, translate requirements into clear project specifications, and provide regular updates on project progress
- Project Execution: Write clear labeling instructions, review data, balance quality/diversity/volume requirements, and improve processes for efficiency
- Vendor Coordination: Manage day-to-day relationships with external vendors and contractors for human data projects, ensuring they deliver high-quality results on time
- Quality Oversight: Implement systematic quality controls and verification processes to ensure data usability and trustworthiness
- Task Development: Create clear, effective task instructions and training materials for human data workers
- Continuous Improvement: Identify opportunities to improve efficiency, quality, and cost-effectiveness in our human data collection processes
- Data Analysis: Create project dashboards, data analysis reports, and analyze project metrics to provide insights to researchers and the Human Data Operations team
- Cross-functional Collaboration: Partner with researchers, engineering teams, and other stakeholders to optimize human data collection processes
You may be a good fit if you
- Exceptional project management skills with demonstrated ability to handle multiple complex projects simultaneously
- Are extremely detail-oriented with strong organizational skills with the ability to analyze information line-by-line
- Have excellent written and verbal communication skills, with the ability to translate technical requirements into clear instructions
- Experience with data collection, labeling, or analysis in technical environments
- Demonstrate strong problem-solving abilities and can navigate ambiguity effectively
- Are responsive and reliable, with a bias toward action and getting things done
- Have experience with data analysis and can work with tools like SQL, Python, Tableau, spreadsheets, or similar
- Are comfortable working in a fast-paced environment with shifting priorities
- Care about developing safe, beneficial AI systems
Strong candidates may also have
- Experience with human data collection and labeling specific to large language models
- Knowledge of data collection, annotation, or labeling practices
- Experience managing vendor relationships or external contractors
- Experience implementing quality control systems for data collection
- Background in a research-oriented organization, working with researchers and engineers
- Experience with prompt engineering or working with large language models
The expected salary range for this position is:
Annual Salary:
$270,000 - $290,000 USD
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.
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