Data Partnerships

Thinking Machines Lab•San Francisco, CA

1d•$175,000 - $475,000•Onsite

About The Position

Thinking Machines Lab's mission is to empower humanity through advancing collaborative general intelligence. We're building a future where everyone has access to the knowledge and tools to make AI work for their unique needs and goals. We are scientists, engineers, and builders who’ve created some of the most widely used AI products, including ChatGPT and Character.ai, open-weights models like Mistral, as well as popular open source projects like PyTorch, OpenAI Gym, Fairseq, and Segment Anything. About the Role As data partnerships lead at Thinking Machines Lab, you'll own the end-to-end pipeline of data procurement for frontier model training, from understanding what our research teams need, to sourcing and closing providers, to managing the quality and delivery of data. You will be the connective tissue between research, legal, and external vendors, making sure the right data reaches the right teams at the right time. This role is ideal for a technical-leaning person who wants to get deep into the data world in service of an ambitious research agenda. You'll need to be comfortable context-switching between planning out the data needed for training runs and negotiating pricing with data vendors. Over time, you'll build the repeatable, scalable processes that allow our data operations to keep pace with the speed of our research.

Requirements

Degree in computer science, artificial intelligence, mathematics, physics, engineering, or similar.
Experience in data pipelines, procurement, and operations, or a similar role.

Nice To Haves

Masters or PhD in computer science, artificial intelligence, mathematics, physics, engineering, or similar.
Experience working with data at or for frontier AI labs, including sourcing, evaluating, and managing large-scale data pipelines.
Experience at a frontier or academic research lab, contributing to research in artificial intelligence.
Familiarity with the data provider landscape and the commercial, legal, and technical considerations involved in data licensing.
Ability to learn new technical domains quickly and operate comfortably in ambiguity.
Strong technical communication, written and verbal.

Responsibilities

Drive and coordinate data procurement initiatives end-to-end, ensuring that complex sourcing efforts are executed efficiently, transparently, and with scientific rigor.
Partner closely with research teams to proactively understand data needs across pre-training, post-training, and evaluation workstreams, staying ahead of the roadmap rather than reacting to requests.
Source, evaluate, and onboard data providers, building and maintaining a pipeline of potential vendors across domains.
Negotiate pricing, licensing terms, and contract structures with data providers, working alongside legal to close agreements that serve our research goals.
Evaluate incoming data alongside researchers, assessing quality and coverage for intended training objectives.
Monitor and manage ongoing data deliveries, including tracking schedules, flagging issues, and ensuring what we receive matches what was agreed upon.
Build repeatable, scalable processes around the full data procurement lifecycle so that sourcing new data becomes faster and more systematic over time.
Translate technical data requirements into actionable plans with clear milestones, keeping teams aligned across research, infrastructure, legal, and external partners.
Synthesize and communicate progress across diverse stakeholders, ensuring the right people are informed at the right time and that nothing falls through the cracks.