Overview As an Applied Scientist in CXBT, you design principled measurement methodologies to evaluate how autonomous agents interact with AWS. You will develop reproducible experiments to uncover why agents make architectural decisions, and reason about cloud service trade-offs with deep domain knowledge. The role blends GenAI, agent evaluation, and developer-experience research to push the boundaries of agent-driven workloads. You will publish findings and collaborate across scientists, engineers, and product managers. This is a mission-driven, fast-paced research role focused on improving customer experience through rigorous science.
Compensation / Benefits- health insurance
- 401(k) matching
- paid time off
- parential leave
- RSUs
- sign-on payments
Responsibilities- Develop novel scientific methodologies for evaluating autonomous, tool-using agents
- Design rigorous, reproducible experiments with causal insights into agent decision-making
- Apply cloud-architecture knowledge to reason about service trade-offs and deployment considerations
- Develop verification and synthesis methods to ensure evidence-grounded conclusions
- Design evaluation metrics for agent-produced outcomes across correctness, robustness, and security
- Publish and present work in ML-focused venues
- Collaborate with scientists, engineers, and product managers to build science-focused systems
- Proficiency in model development, validation and implementation for NLP applications
- Communicate rigorous mathematical concepts clearly to non-experts
- Own the research-to-deployment process from idea to advanced models and agentic systems
Key requirements- 3+ years of building models for business applications
- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- Experience in patents or publications at top-tier conferences or journals
- Programming experience in Java, C++, Python or related language
- Experience with algorithms, data structures, parsing, numerical optimization, data mining, parallel and distributed computing, HPC
- Hands-on experience building ML models for NLP tasks using GenAI
- strong problem-solving ability
- comfort with ambiguity
- attention to detail
- GenAI
- machine learning
- NLP
