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Learning Systems Scientist (AI Systems)
Research
Bellevue, WA
Full-time (Hybrid)
$220,000 - $320,000Team: Learning Systems
About the Role
Regenerative AI builds self-adaptive AI systems that continuously monitor, regulate, and improve their own behavior during real-world operation. Our platform enables feedback-driven adaptation and runtime intelligence for production AI deployments. We are looking for a Learning Systems Scientist to define how our systems learn, adapt, and maintain robustness over time.
What You'll Do
- Design feedback signals and evaluation frameworks for system-level adaptation
- Define and implement metrics for drift detection, stability, and reliability
- Build offline simulators and test harnesses to validate runtime behavior
- Experiment with adaptation mechanisms including routing, state updates, and recalibration
- Partner with ML Engineering to productionize monitoring and guardrails
- Analyze system failures, propose fixes, and validate improvements
- Develop tooling for continuous evaluation of deployed systems
- Contribute to internal standards for system robustness and operational excellence
- Translate ambiguous system behavior into measurable, actionable metrics
Qualifications
- MS or PhD in Computer Science, Machine Learning, or related field
- Strong ML fundamentals combined with systems-level thinking
- Experience with production ML evaluation, monitoring, or observability
- Ability to translate complex system behavior into measurable metrics
- Proficiency in Python and modern ML frameworks (PyTorch or equivalent)
- Comfort with distributed systems and large-scale experimentation
- Strong analytical and problem-solving skills
- Excellent communication and cross-functional collaboration abilities
Nice to Have
- Experience with continual learning, online learning, or adaptive systems
- Background in control theory, optimization, or reinforcement learning
- Familiarity with observability tools, incident response, or reliability engineering
- Experience with causal reasoning or counterfactual evaluation
- Knowledge of data pipelines, streaming systems, or real-time processing
- Experience building internal tools or evaluation frameworks
Benefits & Perks
Competitive salary and meaningful equity
Comprehensive health, dental, and vision insurance
Flexible hybrid work arrangements
Annual learning and development budget
401(k) with company match
Modern tech stack: Python, PyTorch, Docker, cloud (AWS/GCP), observability tools
Visa sponsorship available