Data Operations

Thinking Machines Lab•San Francisco, CA

8d•$250,000 - $350,000•Onsite

About The Position

The mission of Thinking Machines is to build AI that extends human will and judgment. We are training frontier models with Inkling, developing Tinker to let people make models their own, and crafting interfaces that broaden human-AI communication. We believe the future worth building is human, and we're hiring people who want to build it. About the Role We're looking for someone to join Data Operations and help researchers get the data they need to train and evaluate our models. You'll work directly with researchers to understand what they need, figure out how to get it, and own the work through delivery. Sometimes that means finding the right vendor. Sometimes it means digging into a new domain, finding unusual sources of data, or working through a request we haven't seen before. This is a hands-on role. You'll spend time talking directly with vendors, reviewing data quality, and building processes and systems that make the work easier to repeat and scale. Our research priorities change quickly, so the work will too. We're looking for someone who is resourceful, flexible, and comfortable figuring things out as they go.

Requirements

Experience owning operational, data, product, program, or vendor work from start to finish.
Experience working with data vendors ideally in AI or technology.
Strong problem-solving instincts and a willingness to dig in when there isn't an obvious answer.
Comfortable working directly with researchers or technical teams and turning loosely defined needs into action.
Good judgment about quality and a willingness to inspect the work closely rather than rely only on process.
Strong communication skills across different teams, vendors, and cultures.
Comfortable with ambiguity, changing priorities, and tight timelines.
High initiative and willingness to do whatever part of the job is needed to move the work forward.
Able to add useful structure without overcomplicating things.

Nice To Haves

Experience with pre-training, post-training, evaluation, annotation, or other AI data types.
Existing relationships with a diverse set of AI or related data vendors.
Experience at an AI company, data company, marketplace, or other fast-moving technology company.
Experience working with international vendors and cross-border operational or compliance issues.
Product, program, operations, or generalist experience in an environment where you had to build the process as you went.
Experience building simple tooling or automation to reduce manual operational work.

Responsibilities

Work with researchers to understand what data they need and turn open-ended requests into a concrete plan.
Own data projects from sourcing and vendor selection through quality review and delivery.
Find the best vendors, experts, and data sources for different types of work.
Build and maintain strong partnerships with data vendors, including international partners.
Review data with researchers and vendors, identify quality issues, and improve the output.
Go deep on new data domains when needed and quickly learn what good looks like.
Build guidelines, processes, and tools that make recurring work easier and more scalable.
Automate repetitive work where it makes sense while staying close to the work that requires judgment.
Work with legal and other teams on practical ways to manage vendor relationships, and adhere to communication guidelines.
Manage multiple projects against research and model timelines and adjust quickly as priorities change.