Design and implement multi-agent optimization for distributed decision-making
Develop temporal logic frameworks and constraint-satisfaction for planning
Create mathematical models for sequential decision processes under uncertainty
Build computational frameworks balancing algorithmic efficiency with human-interpretable reasoning
Implement and evaluate metrics for algorithm performance and efficiency

🎯 Requirements

BS or MS in CS/SE/Robotics or 5+ years in intelligent agents or planning
5+ years of hands-on C++ development (C++20)
Strong theoretical and practical experience in constraint satisfaction, scheduling, and optimization
Proficiency with Bazel in Docker-based Linux environments
Experience with Docker and Linux (RHEL/Ubuntu)
Ability to translate complex mathematical concepts into clear technical documentation

🎁 Benefits

Health, dental, vision, life and disability insurance
401k retirement with employer match
Learning and wellness stipends
Paid time off

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