Resaro

Senior VP, Reinforcement Learning

Resaro

full-time

Posted on:

Location Type: Hybrid

Location: Munich • Germany

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Job Level

Senior

Tech Stack

IoT

About the role

  • Independently implement Resaro’s RL validation prototype to expose agent instability and vulnerability in a mission-critical and complex environment.
  • Scale, lead and mentor a global, cross-functional, high-performing team of AI researchers and engineers, drawing on experience steering organizations of 30+ experts.
  • Define the long-term vision and technical roadmap for RL TEVV, focusing on validating RL algorithms and learned policies in complex environments with mission-critical applications across system control, autonomous vehicles, and robotics.
  • Advance methods for learning probabilistic reward functions from human feedback (RLHF) to align AI behavior with mission goals.
  • Partner with Product Management to translate product vision, customer problems, and market opportunities into end‑to‑end solution architecture and technical roadmaps that support a product-led growth strategy.

Requirements

  • Master / Ph.D. in Robot Reinforcement Learning or a closely related field.
  • Proven track record in developing and implementing novel RL and ML algorithms, e.g. research or commercial implementation.
  • Demonstrated deep theoretical understanding of and practical experience with the RL framework, including bandit setting, (in-)finite horizon setting, on- and off-policy RL, and trust-region RL approaches.
  • Experience in Bayesian Machine Learning and probabilistic models.
  • Understanding of AI/ML/RL lifecycle and the state-of-the-art approaches and limitations of testing and validating complex use cases.
  • Strong skills in requirements gathering, stakeholder communication, and solution scoping.
  • Experience with fully differentiable deep learning for highly unstable systems (nice-to-have).
  • Experience with Active Learning and RLHF (nice-to-have).
  • Background in model compression and pruning for deploying large RL models onto edge devices (nice-to-have).
  • Hands-on experience with Bayesian Meta-Learning to reduce training time and absolute error in complex models (nice-to-have).
  • A strong portfolio of innovation, including multiple successful paper submissions at conferences like NeurIPS, ICML, ICLR, IROS, ICRA, CoRL, and a deep patent history (e.g., 17+ patents) (nice-to-have).
  • Experience spearheading global AI initiatives and delivering AI solutions for both B2G (Unmanned Systems) and B2B (IoT) sectors (nice-to-have).
  • Demonstrated success in leading cross-functional teams to deliver technical solutions (nice-to-have).
  • Knowledge of deployment constraints in high-security or classified environments (nice-to-have).
  • Prior exposure or experience with directly engaging senior stakeholders from Director to C-suite level (nice-to-have).
  • Prior security clearance at Government CONFIDENTIAL and above (nice-to-have).
Benefits
  • Health insurance
  • Flexible working hours
  • Professional development opportunities
Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools
Reinforcement LearningMachine Learning algorithmsBayesian Machine Learningprobabilistic modelsdifferentiable deep learningActive LearningBayesian Meta-Learningmodel compressionpruningtechnical solution delivery
Soft Skills
leadershipmentoringstakeholder communicationrequirements gatheringsolution scopingcross-functional team leadershipinnovationportfolio developmentengagement with senior stakeholdersproject management
Certifications
Master's degreePh.D.