Senior Reinforcement Learning Engineer
hace 14 días
Tallahassee
Senior Reinforcement Learning Engineer – Bio-Defense & Complex Systems - (US-based only) We’re seeking a Senior Reinforcement Learning Engineer to join an advanced AI-driven technology company solving high-impact, real-world problems in healthcare, insurance, and complex system modeling. This role focuses on designing, implementing, and deploying RL-based decision-making and adaptive control systems in critical bio-defense, claims resilience, and risk-sensitive environments. Role Overview: As a Senior RL Engineer, you’ll work at the intersection of reinforcement learning, simulation, and applied machine learning. You will translate theoretical RL and systems models into operational, production-ready solutions with measurable real-world impact. This is a hands-on role, with autonomy to drive experimentation, training, validation, and deployment of RL and multi-agent systems. Key Responsibilities: • Design, implement, and optimize RL agents for complex, dynamic, and high-stakes environments, • Develop simulation environments (stochastic, agent-based, or hybrid) to train and evaluate RL policies, • Integrate RL models with supervised and unsupervised ML pipelines using structured (tabular) and temporal data, • Evaluate model robustness, generalization, and failure modes under uncertainty or adversarial conditions, • Collaborate with domain experts to formalize reward functions, constraints, and state spaces, • Maintain hands-on involvement in experimentation, deployment, and optimization Required Qualifications: • 4+ years of ML experience, with deep expertise in reinforcement learning, • Strong foundation in MDPs, POMDPs, policy gradients, value-based methods, and model-based RL, • Hands-on experience with RL frameworks such as Stable-Baselines, RLlib, or PyTorch/JAX implementations, • Strong Python skills and experience building end-to-end ML pipelines, • Comfortable working with tabular, time-series, and simulation-generated data Preferred / Nice to Have: • Experience with agent-based modeling, digital twins, or hierarchical/multi-agent RL, • Experience in high-stakes, regulated, or mission-critical environments, • Familiarity with uncertainty modeling, robustness testing, or safety-aware RL What We Value: • Systems-first mindset: thinking beyond models to real-world operational impact, • Ability to work in ambiguous problem spaces with incomplete data, • Strong ownership, technical rigor, and ethical awareness in high-impact AI systems Why Join: • Work on mission-critical AI challenges that directly influence real-world outcomes, • High autonomy and deep technical ownership, • Shape next-generation decision-making and adaptive AI systems Location: Florida/Remote within the US only available. If you’re passionate about reinforcement learning, simulation, and building AI systems with tangible, high-stakes impact, this is an exciting opportunity to make a real difference.