You've unlocked major wins in your career - you've built rigorous behavioral or neuroscience models and shown significant impact as a result. You excel at finding patterns in what people do with products, understanding why, and optimizing user journeys end to end.
Now, imagine scaling your impact across many products and companies, leveling up the entire app ecosystem. Every app in your pocket becomes smarter, more engaging, and more essential to the people who rely on it.
You can help product teams iterate faster, delight users, and grow revenue, all because of the behavioral intelligence you build once and deploy everywhere.
We know this ambition: we've done this again and again at places like Uber, Apple, Google, and Chime. We've had tens of billions of dollars of impact for products essential to billions of people, and we're ready to scale our impact to the next level.
Does this sound like the next chapter you're looking for? If yes, read on.
Palladio AI is an AI platform designed to revolutionize product-led growth and help our customers become a more valued part of their users’ everyday lives.
We're initially focused on mobile gaming, where development moves fastest, users are most engaged, and experimentation has immediate impact. It's the ideal proving ground for our platform.
Our team is building core systems in behavioral modeling, causal inference, forecasting, agentic platforms, and more. You'll help extend those domains: building ML- and AI-based behavioral models to detect and surface product opportunities, and shipping learning loops that improve themselves with every release. Your work will model how users feel, think, decide, and do - translating behavioral signals into opportunities that make products more intuitive, engaging, and rewarding. In short, you'll turn first-principles data science, neuroscience, cognitive science, and machine learning into a product that scales across industries.
Customer-obsessed. You connect with users' pain points, needs, and aspirations throughout user journeys, measure success in user outcomes, and translate findings into more innovative and more engaging product experiences.
Scientific builder. You're fluent in both theory and production, from behavioral model design to the product development process.
Craft and excellence. You dive into messy data, prototype quickly, and iterate until the insight sings.
Impact mindset. You balance scientific rigor with "it ships today, iteration on the way" pragmatism.
Owner at heart. Zero-to-one energizes you; you'd rather set the standard than inherit one.
Beginner's mind. You stay hungry to learn, because better ideas are always out there.
3+ years (or equivalent experience) in applying machine learning in cognitive science, computational neuroscience, behavioral economics, or consumer behavior modeling.
Fluent in deep learning for multimodal time-series data (e.g., behavioral, contextual, transactional, visual, neural).
Our team has shaped the design, data, and systems behind some of the world's most iconic products. We're builders who founded Uber's Michelangelo, led data and design teams at Apple, Google, and Chime, and shipped products used by billions. We've had tens of billions of dollars of impact. Backed by top-tier investors, we're now channeling that experience into a focused, user-obsessed startup so every product team can tap the same class of intelligence at scale.
Now is the moment to have an outsized impact. You'll work directly with founders and early customers to define not just features but also the fundamental approach to how product intelligence should work. You'll see your ideas in production quickly, affecting real decisions for products used by millions.
We're building a company that values clarity, craft, and impact. If those values resonate with you, we'd love to connect.
Build and productize scalable machine learning solutions using LLMs and real-world data, partnering with clients and teammates to prototype ideas and deliver production-ready services.
Develops and productionizes machine learning and GenAI solutions, improving data pipelines and existing code while collaborating across data and application teams to deliver reliable, scalable capabilities.
Build and improve production machine-learning solutions by exploring data, shaping product experiments, and developing end-to-end pipelines in collaboration with Product Owners, Data Scientists, and Engineers.
Develop and own deep learning R&D for computer vision, designing and implementing algorithms, improving model performance, and applying advances in AI to 2D and 3D vision technologies.
Build and improve production machine learning systems, developing scalable data pipelines, deep learning and time-series models, agentic workflows, and monitoring processes for model performance.
