AI Research Engineer - Reinforcement Learning
Tasks
- Build execute and evaluate reinforcement learning experiments
- Define success metrics and monitor deployed reinforcement learning systems
- Design reinforcement learning algorithms to optimize decision-making in simulated and real environments
- Develop simulation environments and training datasets
- Document experimental findings and technical approaches
- Improve policy performance convergence stability and sample efficiency
- Integrate reinforcement learning agents into production systems
- Optimize reinforcement learning pipelines for exploration policy stability reward efficiency
Perks/Benefits
- Career growth opportunities
- Flexible work culture
- Fully remote
- Global collaboration
- Innovation-focused environment
Skills/Tech-stack
Actor-critic | Data Pipelines | Exploration/exploitation | Large-scale | Large-scale experimentation | Multi-Modal | Multi-modal AI | Online Reinforcement Learning | Policy Optimization | Policy gradients | PyTorch | Reinforcement Learning | Reward Optimization | Sample efficiency | Simulation Environments | Training Data Pipelines | Training data
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
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