Overview As a Senior Applied Scientist, you will own the scientific roadmap for personalization initiatives in a new domain of persistent, compounding memory. You will guide cross-functional teams from problem formulation to production impact, shaping the research agenda and evaluating novel knowledge systems. You'll mentor junior scientists and translate research into architectural decisions that influence product direction. This role offers the opportunity to lead a pioneering effort in a fast-moving, experimentation-driven environment. You will work closely with engineering leadership to balance scientific rigor with business impact and publish advancements in top venues.
Compensation / Benefits- health insurance (medical, dental, vision)
- 401(k) matching
- paid time off
- parental leave
- RSUs
- sign-on payments
Responsibilities- Define the scientific roadmap for knowledge acquisition, representation, and retrieval at organizational scale
- Lead research on how AI systems should learn from experience - what to capture, how to generalize, when to forget
- Design evaluation frameworks for a system where quality means right knowledge, context, and confidence
- Own end-to-end research from problem formulation through production impact measurement
- Mentor Applied Scientists and establish scientific standards for a new team
- Partner with engineering leadership to translate research into architecture decisions that shape the product
- Drive technical decisions on model architecture, training methodology, and evaluation frameworks, balancing scientific rigor with business impact
- Publish at top-tier venues and advance the state of the art in applied knowledge systems
Key requirements- 4+ years of applied research experience
- 3+ years of building machine learning models for business applications
- PhD, or Master's degree and 6+ years of applied research experience
- Experience programming in Java, C++, Python or related language
- Experience with neural deep learning methods and machine learning
- leadership and mentoring
- ability to translate ambiguous problems into ML formulations
- strong cross-functional collaboration
- Java
- C++
- Python
