AI Research Engineer - Reinforcement Learning

This position is posted by Jobgether on behalf of a partner company. We are currently looking for an AI Research Engineer - Reinforcement Learning in Israel. This is an exciting opportunity to work at the forefront of artificial intelligence research, developing advanced reinforcement learning systems designed for real-world applications. The role focuses on building intelligent, adaptive AI models capable of optimizing decision-making across dynamic and complex environments. As part of a globally distributed research team, you will contribute to cutting-edge experimentation involving large-scale reinforcement learning, multi-modal architectures, and resource-efficient AI systems. You will collaborate closely with researchers, engineers, and cross-functional teams to design, test, and deploy innovative RL algorithms that push the boundaries of model performance and scalability. The position combines deep technical research with hands-on implementation, making it ideal for professionals passionate about solving complex AI challenges. This role offers the opportunity to shape next-generation AI capabilities within a highly innovative, remote-first environment. Accountabilities • Design, develop, and implement advanced reinforcement learning algorithms to optimize decision-making processes across simulated and real-world environments. • Build, execute, monitor, and evaluate large-scale reinforcement learning experiments while tracking key performance indicators and benchmark results. • Develop and curate high-quality simulation environments and training datasets tailored to domain-specific reinforcement learning challenges. • Optimize reinforcement learning pipelines by identifying and resolving issues related to exploration strategies, policy divergence, reward signal instability, and computational efficiency. • Improve policy performance, convergence stability, and sample efficiency through advanced optimization techniques and iterative experimentation. • Collaborate with engineering and research teams to integrate reinforcement learning agents into production systems and real-world applications. • Define measurable success metrics and continuously monitor deployed RL systems to ensure robustness, scalability, and sustained performance improvements. • Contribute to ongoing AI research initiatives by exploring innovative RL methodologies, model architectures, and training frameworks. • Document experimental findings, technical approaches, and research outcomes to support knowledge sharing and continuous innovation. Requirements • Degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field; PhD preferred. • Strong research background in reinforcement learning, machine learning, NLP, or AI-related disciplines with proven contributions to advanced AI research initiatives. • Hands-on experience conducting large-scale reinforcement learning experiments, including online RL methods such as Group Relative Policy Optimization (GRPO). • Deep understanding of reinforcement learning concepts including policy gradients, actor-critic methods, GRPO, exploration-exploitation tradeoffs, and policy optimization techniques. • Strong expertise in PyTorch and reinforcement learning frameworks, including experience building end-to-end RL pipelines. • Experience developing, training, evaluating, and deploying reinforcement learning systems in production or large-scale research environments. • Proven ability to solve complex RL challenges such as sample inefficiency, training instability, reward optimization, and convergence issues. • Experience working with multi-modal AI systems and resource-efficient model architectures is considered a strong advantage. • Strong analytical, problem-solving, and experimentation skills with a research-driven mindset. • Excellent communication and collaboration abilities within distributed and cross-functional teams. Benefits • Fully remote work environment with global collaboration opportunities. • Opportunity to work on cutting-edge AI and reinforcement learning technologies. • Exposure to advanced multi-modal architectures and large-scale AI research initiatives. • Flexible and innovation-focused work culture that encourages experimentation and continuous learning. • Collaboration with highly skilled international AI researchers and engineers. • Opportunity to contribute to impactful AI systems with real-world applications. • Career growth opportunities within a rapidly evolving global technology environment. • Dynamic and fast-paced setting focused on innovation, research excellence, and technical ownership. How Jobgether Works We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether? Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.