Senior Expert/VP Reinforcement Learning at Resaro AI

Munich, Bavaria, Germany -

Full Time

Start Date

Immediate

Expiry Date

30 May, 26

Salary

0.0

Posted On

01 Mar, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Reinforcement Learning, AI Testing, Validation, Verification, Autonomous Driving, Robotics, Agent Instability, Agent Vulnerability, RLHF, Probabilistic Reward Functions, Solution Architecture, Bayesian Machine Learning, Probabilistic Models, Stakeholder Communication, Solution Scoping, Meta-Learning

Industry

Software Development

Description

Resaro builds advanced AI testing software to help organizations verify, validate, and trust their most critical AI systems — from computer vision to generative AI and autonomous systems. Our mission is to ensure that AI technologies deployed in real-world, high-stakes environments are robust, explainable, and secure. We work closely with our customers through embedded delivery teams who operate on-site or in close collaboration. These teams tailor solutions to specific mission needs, helping organizations — especially in the public safety and national security sectors — evaluate and improve the performance of their AI-enabled systems. About the Role: As the Senior Expert/ VP Reinforcement Learning, you will be the primary architect of our AI Test, Evaluation, Verification, and Validation (TEVV) product suite for reinforcement learning systems. You will lead the development of next-generation AI testing and assurance frameworks with applications in Autonomous Driving and Robotics. Your mission is to scale our capabilities in Reinforcement Learning, to ensure autonomous agents are safe, robust, and explainable in the field. Key Responsibilities 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. Must-Have Skills and Experience 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. Nice-to-Have Experience with fully differentiable deep learning for highly unstable systems. Experience with Active Learning and RLHF. Background in model compression and pruning for deploying large RL models onto edge devices. Hands-on experience with Bayesian Meta-Learning to reduce training time and absolute error in complex models. 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). Experience spearheading global AI initiatives and delivering AI solutions for both B2G (Unmanned Systems) and B2B (IoT) sectors. Demonstrated success in leading cross-functional teams to deliver technical solutions. Knowledge of deployment constraints in high-security or classified environments. Prior exposure or experience with directly engaging senior stakeholders from Director to C-suite level. Prior security clearance at Government CONFIDENTIAL and above. Why Join Resaro Work on mission-critical AI systems in defence, aerospace, and public safety. Help define the future of AI testing and assurance in real-world environments. Collaborate with a tight-knit, expert team working at the intersection of AI, systems engineering, and policy. Shape product direction while being close to the operational reality of AI deployments. Resaro is an Equal Opportunity Employer. We respect each individual and support the diverse cultures, perspectives, skills and experiences within our teams. Location Munich (Hybrid) Department Embedded Team - DE Employment Type Full-Time Minimum Experience Senior Manager/Supervisor

Responsibilities

The role involves independently implementing the RL validation prototype to expose agent instability and defining the long-term vision and technical roadmap for RL Test, Evaluation, Verification, and Validation (TEVV). Key duties include scaling, leading, and mentoring a global team of AI researchers and engineers, and advancing methods for learning probabilistic reward functions from human feedback.