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
As a Product Manager for the Research organization at Anthropic, you will own the ideation and deployment of new products as we advance frontier, safe AI technology. Research product managers’ primary mission is to make Anthropic’s models and research–the underlying magic of all of our products– delight end users and builders. We partner with our world class researchers on developing new versions of Claude and bringing advanced versions of research to market including Golden Gate Claude and Computer Use. You will work closely with our research teams to help productize applied research and identify high-potential use cases grounded in customer needs.
We are looking for someone passionate about developing safe and beneficial artificial intelligence technologies. You should have experience rapidly prototyping and launching innovative technologies and products that open imaginations and possibilities. You thrive in ambiguous environments and exercise good judgement in high stakes situations.
Responsibilities:
- Lead vision, strategy, roadmap and execution of frontier technologies that leverage the latest AI capabilities to solve real-world problems
- Rapidly prototype and experiment with different products and services to validate product market fit
- Act as the voice of the customer, embrace user feedback and synthesize insights into actionable product requirements, user stories, and product specifications
- Analyze metrics to inform future product development
- Understand AI landscape and ecosystem, ensuring we have an objective view of market capabilities and our position
- Ability to work and influence across a diverse set of stakeholders, including researchers as well as product engineering and platform engineering
You may be a good fit if you have:
- 5+ years in product management, experience launching new products and scaling existing products
- Technical background with experience working cross functionally with engineering teams to ship technical products
- Experience working with or applying Large Language Models in products
- Experience in the AI or machine learning industry
- Data-driven mindset with Python and SQL working proficiency a must
- The ability to navigate and execute amidst ambiguity, and to flex into different domains based on the business problem at hand, finding simple, easy-to-understand solutions
- Track record of launching products that have found distribution or commercial success
- Excitement for engaging in cross-organizational collaboration, working through trade-offs, and balancing competing priorities
- Ability to clearly articulate complex technical concepts to non-technical audiences in written and verbal communication
- Passion for using AI to create safe and beneficial products
- Think creatively about the risks and benefits of new technologies, and think beyond past checklists and playbooks
- You stay up-to-date and informed by taking an active interest in emerging research and industry trends
- Have a creative hacker spirit and love solving puzzles
Deadline to apply: None. Applications will be reviewed on a rolling basis.
The expected salary range for this position is:
Annual Salary:
$305,000—$385,000 USD
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.
Top Skills
What We Do
Anthropic is an AI safety and research company that’s working to build reliable, interpretable, and steerable AI systems. Our research interests span multiple areas including natural language, human feedback, scaling laws, reinforcement learning, code generation, and interpretability.
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