AI Developer for Reinforcement Learning & Autonomous Vehicle Simulation
Budget: $15 – $25 AUD
I am on the lookout for a seasoned AI developer to join me in a project centered around reinforcement learning and autonomous vehicle simulation. The main task will be to embed and evaluate deep reinforcement learning (DRL) algorithms within a high fidelity simulated driving environment that mirrors real-world physics in detail.
Key Responsibilities:
- Implementing Deep Q-Network (DQN) and Proximal Policy Optimization (PPO) algorithms.
- Thoroughly testing these algorithms for performance and reliability.
- Collaborating on optimizing the simulation for high fidelity.
The ideal candidate should:
- Have a strong command of Python.
- Be well-versed in using the CARLA simulator.
- Possess substantial experience in reinforcement learning, autonomous systems, and AI.
- Have a good understanding of detailed physics and able to simulate complex scenarios.
Your expertise will directly contribute to the development of a robust autonomous driving system. If you have a passion for AI and autonomous systems, and have the skills to match, I would love to hear from you.
Key Responsibilities:
- Implementing Deep Q-Network (DQN) and Proximal Policy Optimization (PPO) algorithms.
- Thoroughly testing these algorithms for performance and reliability.
- Collaborating on optimizing the simulation for high fidelity.
The ideal candidate should:
- Have a strong command of Python.
- Be well-versed in using the CARLA simulator.
- Possess substantial experience in reinforcement learning, autonomous systems, and AI.
- Have a good understanding of detailed physics and able to simulate complex scenarios.
Your expertise will directly contribute to the development of a robust autonomous driving system. If you have a passion for AI and autonomous systems, and have the skills to match, I would love to hear from you.