Pebble - AI Research Engineer - Reinforcement Learning

Key Responsibilities :

- RL Algorithm Development : Design, develop, and implement state-of-the-art RL algorithms to solve complex, real-world problems.

- Full-Stack AI Engineering : Manage the entire lifecycle of RL systems, from data engineering and model architecture to training, deployment, and performance monitoring.

- Performance Engineering : Identify and address bottlenecks in RL training pipelines to optimize performance and efficiency.

- Hyperparameter Tuning : Tune reward functions, hyperparameters, and exploration strategies to ensure robust and effective learning.

- Research & Collaboration : Collaborate on research projects and integrate new RL algorithms into existing products and platforms.

Required Qualifications :

- 8+ years of experience in Python programming.

- Proven experience in full-stack engineering for machine learning systems, from data handling to model deployment.

- Expertise in performance engineering for RL training.

- Demonstrated experience in tuning RL components (reward functions, hyperparameters, exploration strategies) to solve complex tasks.

- Strong understanding of RL theory and practical implementation.

Nice to Have :

- An advanced degree (MS or PhD) in Computer Science or a related field.

- Experience with Kubernetes (k8s), Docker, GPU Performance / systems engineering, and model inference optimization.