AI Research Engineer - Reinforcement Learning
Tasks
- Build and evaluate large scale reinforcement learning experiments
- Create simulation environments and training datasets
- Define success metrics and monitor deployed reinforcement learning systems
- Develop reinforcement learning algorithms for decision optimization
- Document experimental findings and technical approaches
- Improve policy performance convergence and sample efficiency
- Integrate reinforcement learning agents into production systems
- Optimize reinforcement learning pipelines and troubleshoot issues
- Research new reinforcement learning methodologies and model architectures
Perks/Benefits
Skills/Tech-stack
Actor-critic | Computer simulation | Deep learning | Exploration/exploitation | Group Relative Policy Optimization | Language Processing | Machine Learning | Multi-Modal | Multi-modal Machine Learning | Natural Language | Natural Language Processing | Online Reinforcement Learning | Policy Convergence | Policy Optimization | Policy gradients | PyTorch | Reinforcement Learning | Sample efficiency
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
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