Product Manager

Job description

## About the Company Models are what they eat. But a large portion of training compute is wasted training on data that are already learned, irrelevant, or even harmful, leading to worse models that cost more to train and deploy. At DatologyAI, we’ve built a state of the art data curation suite to automatically curate and optimize petabytes of data to create the best possible training data for your models. Training on curated data can dramatically reduce training time and cost (**7-40x faster training** depending on the use case), dramatically increase model performance **as if you had trained on >10x more raw data** without increasing the cost of training, and allow smaller models with **fewer than half the parameters** to outperform larger models despite using far less compute at inference time, substantially reducing the cost of deployment. For more details, check out our recent research on synthetic data scaling ([BeyondWeb](https://www.datologyai.com/blog/beyondweb)) and pretraining with domain-specific data ([The Finetuner’s Fallacy](https://www.datologyai.com/blog/finetuners-fallacy)). We raised a total of $57.5M in two rounds, a Seed and Series A. Our investors include Felicis Ventures, Radical Ventures, Amplify Partners, Microsoft, Amazon, and AI visionaries like Geoff Hinton, Yann LeCun, Jeff Dean, and many others who deeply understand the importance and difficulty of identifying and optimizing the best possible training data for models. Our team has pioneered this frontier research area and has the deep expertise on both data research and data engineering necessary to solve this incredibly challenging problem and make data curation easy for anyone who wants to train their own model on their own data. This role is based in San Mateo, CA. We are in office 4 days a week. ## About the Role As our first Product Manager, you will own the product strategy and roadmap for our enterprise data curation platform. This is a high-leverage, high-ownership role where you’ll build the function from the ground up. You'll work at the intersection of cutting-edge ML research and enterprise software, translating deep technical capabilities like automated data selection, deduplication, batching, multimodal curation at petabyte scale into a product that enterprise AI teams love to use. You'll partner closely with the founders, our research, engineering teams to define what we build and why. This role will shape how Datology evolves from a technically differentiated platform into a category-defining AI tooling company. ## What You'll Work On - Own the product roadmap end-to-end: from discovery and prioritization through launch and iteration, with a focus on enterprise-grade AI tooling - Partner with research and engineering to turn ambiguous, early-stage outputs into concrete, shippable product decisions. - Define and drive the enterprise product experience -- including platform UX, API design, deployment flexibility (BYOC, on-prem), and integrations with existing ML workflows - Develop deep customer intuition by engaging directly with enterprise ML teams, data scientists, and infrastructure engineers -- turning their pain points into a clear product strategy - Build the foundational PM infrastructure: discovery frameworks, roadmap tooling, release processes, and cross-functional rituals that scale as the team grows - Work with Sales and Customer Success to ensure the product enables a repeatable, defensible go-to-market motion - Track the competitive landscape across AI tooling, MLOps, and data infrastructure to inform positioning and prioritization - Serve as the connective tissue between research output and commercial product -- helping the team decide what to build, sequence how, and measure whether it's working ## About You - 5+ years of product management experience, with at least 3 years building enterprise software or AI/ML tooling at a senior or staff level - A strong technical foundation. You can read a research paper, engage credibly with ML engineers about training pipelines and data infrastructure, and distinguish meaningful technical differentiation from noise - You've shipped products where the starting point was a paper or prototype and know how to impose structure without killing what makes the technology special - Experience as a founding or early PM, with a track record of building product functions and processes - Deep familiarity with the enterprise AI/ML buyer: you understand how ML teams evaluate tools, what makes them adopt and stick, and how infrastructure decisions get made - A sharp product instinct for developer and technical user experiences. You know the difference between a product that's powerful and one that's actually used - Excellent cross-functional communication: you can make a research result legible to a sales team and a customer complaint actionable for an engineer - Comfort operating in ambiguity and a bias toward decisive, data-informed action **Bonus points if you have:** - Hands-on experience with model training, data pipelines, or MLOps workflows - Prior experience at an AI infrastructure, developer tools, or data platform company - Exposure to enterprise procurement and compliance requirements (BYOC, on-prem, data sovereignty) **Don’t meet every single requirement?** We still encourage you to apply. If you’re excited about our mission and eager to learn, we want to hear from you! ## Compensation At DatologyAI, we are dedicated to rewarding talent with competitive salary and meaningful equity. The salary for this position ranges from $215,000 to $300,000. - Starting pay is based on job-related skills, experience, qualifications, and interview performance. ## Benefits - 100% covered health benefits (medical, vision, and dental). - 401(k) plan with a generous 4% company match. - Unlimited PTO policy - Paid Parental Leave of 12 weeks, plus 6 months of WFH flexibility. - Annual $2,000 wellness stipend. - Annual $1,000 learning and development stipend. - Daily lunches and snacks are provided in our office! - Relocation assistance for employees moving to the Bay Area. ##