Research Operations, Partnerships

Key Skills

Operations, Aartificial intelligence, Machine learning techniques, Effective communication skills

Job Description

The role of Research Operations, Partnerships within the LLMO/Tokens team at Anthropic coordinates and enables our teams to be the best at what they do and to make fast-paced progress towards our mission. We continually pursue scalable and sustainable ways to optimize work on real world applications, cultivating an environment where people can be both highly collaborative and deeply creative, making responsible and pioneering research progress at pace. We build strong relationships with teams and team members (internally & externally), bringing clarity to ambiguity as it relates to data needs. We continually deepen our domain knowledge, working alongside engineers, researchers, and product managers to execute on programs and projects within Anthropic.

The LLMO/Tokens team collaborates with product and research teams inside Anthropic to incubate groundbreaking research and deploy advanced machine learning algorithms to improve Anthropic products and services. This role will work closely with cross-functional teams to deliver research solutions across Anthropic. In the role of Research Operations, Partnerships, you will be primarily responsible for a broad set of data partnerships that add value to multiple initiatives, delivering sustainable change to meet objectives.

Responsibilities:

• Lead and drive delivery of cross-functional partnerships designed to achieve highly impactful applications of machine learning
• Work with cross-functional partners to organize and optimize work into clear goals and objectives
• Partner closely with cross-functional team members, leading as a strategic thought partner with regard to required data partnerships
• Facilitate conversations, meetings and opportunities for collaboration within relevant Anthropic teams, to drive the best outcomes; create connections and relationships
• Evaluate and improve processes, tools, templates and documentation for repeatability and sustainability
• Learn new business and technical knowledge quickly, adapt to changing environments while providing day-to-day coordination and communication so work moves forward
• Independently perform due diligence to evaluate what kind of data partnerships are required and will be impactful

You might be a good fit if you:

• Have extensive knowledge and expertise in data partnerships, are able to navigate through ambiguity and adjust and adapt plans and strategies as project conditions change
• Have the ability foster respect, inclusion, and collaboration when working with teams, and skilled in building relationships and fostering trust with a diverse group of people
• Have excellent communication skills, with the ability to distill complex ideas to their essence
• Are proactive about learning and acquiring knowledge to enhance your domain knowledge
• Have an understanding of data partnerships, licensing, or equivalent working knowledge
• Have knowledge of or are curious to learn about AI / machine learning research

Strong candidates may also have:

• BS/BA in a relevant field or equivalent experience
• Knowledge of the data licensing landscape or equivalent knowledge of certain media sectors
• Basic understanding of the AI landscape, or content landscape broadly as it pertains to AI

The expected salary range for this position is:

Annual Salary:

$190,000—$230,000 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.