Sr. Applied Scientist, C360
Core
Lead research direction for a new AI system providing persistent, compounding memory and personalization, defining the scientific roadmap and translating ambiguous problems into ML formulations.
Role type
Senior Applied Scientist (Research Lead)
Builds
End-to-end systems spanning knowledge acquisition, retrieval, and reasoning for personalization at organizational scale.
Domain
AI/ML, Personalization, Knowledge Systems
Deliverable
production ML models
Required skills
Machine learning model building, neural deep learning, Java/C++/Python programming, research roadmap definition, experimental design, statistical modeling, model architecture design, evaluation framework design, mentorship
Preferred skills
Large scale distributed systems, modeling tools (R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy)
Technologies
Java, C++, Python, R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy, Hadoop, Spark
Responsibilities
Define scientific roadmap for knowledge acquisition and retrieval; Lead research on AI learning from experience; Design evaluation frameworks for new quality metrics; Own end-to-end research from formulation to production impact; Mentor Applied Scientists; Partner with engineering on architecture decisions; Drive technical decisions on model architecture and training; Publish at top-tier venues
Seniority
Senior, hands-on IC with mentorship responsibilities