About the Role
This position centers on advancing real-time learning and efficiency in intelligent systems, leveraging synthetic data optimization, gradient-free methods, and interface co-design to create adaptive AI that evolves through interaction.
Responsibilities
- Develop and refine product-integrated algorithms that dynamically respond to real-time feedback and system signals
- Create novel feedback mechanisms that enhance algorithmic performance and learning quality
- Work jointly across software, hardware, and algorithm teams to improve end-to-end system efficiency
- Focus measurement on outcomes that reflect tangible, real-world impact
- Ensure algorithmic designs prioritize interaction with live environments, reinforcing the importance of product integration
Benefits
- Flexible work model combining in-person collaboration in the Bay Area with a globally distributed team and periodic offsites
- Annual travel allowance to visit a country you've never been to, supporting personal growth and global perspective
- Weekly stipend for meals, applicable to takeout or grocery delivery
- Full medical coverage and generous paid leave to support health and well-being
Work Arrangement
Hybrid — Bay Area
Our research principles
- Prioritize precision and depth: Achieve technical excellence by tightly integrating algorithms, serving infrastructure, and user interface into a single, optimized system
- Act with urgency and focus: Deliver breakthroughs by concentrating effort on high-impact research directions where innovation meets measurable outcomes
- Measure what drives progress: Validate research through functional systems that enhance user capabilities, prioritizing real-world utility over publication volume
The role
- Position is research-driven with a clear focus on creating tangible, real-world impact
- Core innovation areas include system efficiency, gradient-free optimization, real-time learning, and interface co-design
- Emerging capabilities in synthetic data generation now allow optimization of data spaces, making them dynamic and malleable
- Synthetic data can be shaped to highlight underrepresented or previously inaccessible domains
- Future intelligence systems must interact continuously with the environment, requiring researchers to focus on interaction dynamics
- If these challenges align with your interests, we welcome your application
About us
- Most artificial intelligence systems today lack adaptability and remain static after deployment
- Our mission is to develop intelligence that updates and improves continuously in real time
- We envision AI that is adaptable, personalized, and broadly accessible
- Efficiency is central to scalability and equitable access, ensuring advancements benefit a wide population
- We emphasize talent density by assembling a team of highly motivated, exceptional individuals
- We seek innovators and builders ready to define the future of adaptive intelligence
Other
Applications are encouraged even if not all qualifications are met
