Overview
Friday Systems builds AI that allows industrial robots to adapt to dynamic warehouse environments. Own the DRL stack end-to-end : formulation → algorithm design → large-scale training → evaluation → deployment. Design & ship DRL algorithms (PPO / SAC / DDQN and variants, based on encoders / cross-attention / pointer networks) for complex control & combinatorial optimization. Responsibilities
Implement DRL algorithms (PPO / SAC / DDQN and variants, based on encoders / cross-attention / pointer networks) for complex control & combinatorial optimization. GAE, normalization, entropy / KL control, distributional / value-loss tuning, curriculum learning and reward shaping. Launch multi-GPU training, parallel rollouts, efficient replay / storage, and reproducible experiment tooling. Productionize : clean PyTorch code, profiling, Dockerized services (FastAPI), AWS deployments, experiment tracking, dashboards. Provide mentorship and leadership to foster a culture of quality and innovation. Ownership : you’re comfortable being the primary owner for experiments, code quality, and results in a small team. Deep technical session with CTO on your past RL work (no LeetCode, no homework). Qualifications
Extensive Deep Learning, Reinforcement Learning & PyTorch expertise : You can implement several DRL algorithms from scratch, reason about root‑cause performance drops and make informed decisions about next steps. Python, Linux, Docker, Multi‑GPU, Cloud (AWS). We are not considering entry-level or coursework‑only profiles for this role.
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Aws Engineer • Madrid, Madrid, España