Brain Co. is an applied AI startup co-founded by Jared Kushner and Elad Gil, and backed by leading Silicon Valley builders including Patrick Collison and Andrej Karpathy.
We are building AI applications for the world’s most important institutions, delivering impact on real-world problems across governments, healthcare systems, and critical industries.
Our progress so far:
Automated construction permitting for a sovereign government → 80% faster, unlocking $375M+ in value
Optimized supply chains for a leading global energy company → 30% lower cost, 99% reliability, preventing $100M+ in losses
Streamlined hospital patient care across national health systems → 40% better outcomes, 80% less admin work
Company momentum:
Raised a $55M Series A from leading investors
Built a team of 70+ AI experts from Tesla, Google DeepMind, NVIDIA, and Databricks
At Brain Co., we focus on applying frontier AI to real institutional challenges, working alongside governments, healthcare systems, and critical industries to modernize how essential services operate.
We are looking for leaders who want to help bring new technology into institutions that impact millions of people.
Brain Co. is looking for a TPM to own the end-to-end labeling process across our AI/ML initiatives. This person will serve as the single point of ownership for labeling operations, partnering closely with ML engineers, labelers, vendors, and subject matter experts to ensure high-quality labeled data is delivered efficiently, on time, and at scale.
This is a highly cross-functional role for someone who combines strong operational ownership with technical fluency. You will design and improve labeling workflows, manage the people and processes behind them, and continuously raise the bar on quality, speed, and scalability.
Own labeling operations end-to-end across multiple AI/ML projects
Source, interview, onboard, and manage labelers, agencies, and subject matter experts
Write, refine, and maintain clear labeling instructions, examples, and task definitions
Partner with engineers to determine the right labeling approach, including inputs, outputs, workflows, and quality requirements
Identify and organize the right data and example sets for labeling
Keep labeling work on track against project milestones and proactively communicate risks, blockers, and tradeoffs
Monitor quality, accuracy, and efficiency, and drive corrective actions when gaps appear
Recommend the right tools for data collection and labeling, and help shape lightweight in-house tooling or automation where needed
Facilitate collaboration between engineering and labeling teams to ensure alignment on scope, quality, and timelines
Own dataset curation workflows end-to-end, including working with production data, public data sources, and external SMEs
Build and improve long-term labeling processes with a focus on efficiency, latency, accuracy, and scalability
2+ years of experience in dataset curation, data labeling operations, data annotation, or a similar role
Strong ownership mindset and comfort serving as the point person for a complex workflow
Excellent written communication skills, with the ability to create precise and usable instructions
Strong organizational and project management skills, with the ability to plan around timelines and dependencies
Proactive communicator who raises issues early and helps unblock progress
Sufficient technical knowledge to work effectively with ML and engineering teams
Experience interviewing, managing, or coordinating labelers, vendors, or subject matter experts across different domains
Comfort with lightweight scripting, prototyping, or automation to streamline workflows
Experience working with ML, data, or human-in-the-loop workflows
Familiarity with labeling platforms, annotation tooling, and QA processes
Experience in complex or regulated domains such as health, insurance, or permitting
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