Technical Program Manager, Training Data at Brainco

ABOUT BRAIN CO. 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. ABOUT THE ROLE 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. WHAT YOU’LL DO - 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 QUALIFICATIONS - 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 PREFERRED QUALIFICATIONS - 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