Reinforcement Learning Research Engineer – Exploration & Decision Intelligence (m/w/d)
Tasks
- Build autonomous robotic systems
- Collaborate with simulation and autonomy teams
- Define and implement deep reinforcement learning use cases on edge devices
- Develop decision making for intelligent behavior
- Research and prototype reinforcement learning algorithms
- Translate reinforcement learning theory into scalable systems
Perks/Benefits
Skills/Tech-stack
Agent systems | Attention Mechanisms | C# | C++ | CARLA | Decision Processes | Deep reinforcement learning | Edge Computing | Experiment design | Gazebo | Git | Graph Neural Networks | Isaac Sim | MLflow | Machine Learning | Machine Learning Pipelines | Markov Decision Processes | Mujoco | Multi-Agent | Multi-Agent Systems | Neural Networks | Partially Observable Markov Decision Processes | Policy gradients | PyTorch | PyTorch Lightning | Python | Q-learning | ROS | ROS2 | Reinforcement Learning | Simulation | Statistics | Transformers | Value iteration | Version control
Education
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