Overview In this founding Applied Scientist role, you will lead research and development of AI memory and knowledge retrieval systems. You define the direction, run large-scale experiments, and ship production-ready solutions. You'll build novel approaches to extract knowledge, manage temporal memory, and surface relevant information at the right time. You'll collaborate across engineering, science, and product teams to turn research into impact for customers and the business.
Compensation / Benefits- sign-on payments and RSUs
- health insurance (medical, dental, vision, prescription)
- 401(k) matching
- paid time off
- parential leave
- EAP and mental health support
Responsibilities- Design and implement novel knowledge extraction from heterogeneous data at organizational scale
- Build retrieval systems aligning intent with knowledge across domains
- Own memory generation quality: capture, structure, surfacing, and decay decisions
- Run large-scale experiments using Amazon compute infrastructure and real-world data
- Create evaluation frameworks for quality metrics involving context and confidence
- Collaborate with engineers to move from prototype to production rapidly
- Develop approaches to temporal knowledge management and memory aging
- Publish and patent novel knowledge acquisition and retrieval methods
Key requirements- 3+ years building models for business applications
- PhD, or Master's degree and 4+ years in CS, CE, ML or related field
- Programming experience in Java, C++, Python or related language
- Experience in algorithms, data structures, parsing, numerical optimization, data mining, parallel and distributed computing, HPC
- Experience designing experiments and performing statistical analysis
- Patents or publications at top-tier venues or journals
- collaboration across scientists, engineers, and product managers
- clear communication and stakeholder influencing
- mentoring junior team members
- machine learning and AI for knowledge retrieval and LLMs
- information retrieval and knowledge representation
- temporal knowledge management and memory systems
