at Anthropic
Location
San Francisco, CA | New York City, NY
Compensation
$270k–$365k USD
Type
full time
Posted
1 months ago
Remote
Yes
Market range · company + function + seniority
p25 · target · p75 · n=18
Posted $365k · below the band
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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.
As Data Operations Manager, you'll build and scale data operations across research teams working on frontier AI capabilities. You'll partner with researchers to design and execute data strategies, manage vendor relationships, and own the entire data pipeline from requirements to production. This role requires operational excellence combined with technical depth to understand what makes high-quality training data, but your focus will be on strategy and execution.
The data operations you build will directly determine how well our models perform on critical capabilities—tool use accuracy, prompt injection robustness, long-horizon reasoning, and safety alignment. You'll work with world-class researchers advancing the frontier while building the operational infrastructure to scale these efforts.
We're looking for someone who gets excited about the challenge of scaling quality across diverse research areas—someone who can understand nuanced technical requirements, build the right partnerships, and execute flawlessly. If you thrive at the intersection of operational excellence and cutting-edge AI research, we'd love to hear from you.
Own and execute data strategy for research teams advancing frontier AI capabilities across RLHF, safety, tool use, and agentic workflows
Drive strategic vendor partnerships and build scalable frameworks for technical data collection at scale
Design and implement operational systems that translate research requirements into high-quality data pipelines
Build evaluation frameworks and quality standards that ensure data meets the bar for training state-of-the-art AI systems
Lead cross-functional initiatives to optimize research velocity while maintaining rigorous quality standards
Proactively identify risks, bottlenecks, and opportunities to improve efficiency and effectiveness across data operations
Partner with senior research leaders to align data operations with model development roadmaps and strategic priorities
Have 3+ years in operations, consulting, product management, or program management roles
Have exceptional project management skills with ability to handle multiple complex projects simultaneously
Have strong communication skills and can engage effectively with technical and non-technical stakeholders
Are familiar with how LLMs work or have strong interest in understanding AI training methodologies
Are highly organized and can navigate ambiguity effectively
Have experience with data analysis tools (SQL, Python, Tableau, spreadsheets, or similar)
Thrive in fast-paced research environments with shifting priorities
Are passionate about AI safety and understand the critical importance of high-quality data
Experience with data collection, labeling, or annotation operations for AI/ML systems
Knowledge of RLHF, constitutional AI, or human-in-the-loop workflows
Background working with research teams at AI companies or research-oriented organizations
Experience managing vendor relationships or external contractors
Consulting background with experience translating complex requirements into deliverables
Track record of implementing process improvements or quality control systems at scale
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.
Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience
Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience
Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position
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.
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.
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.
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.
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