Principle Engineer -In Bayesian, Large Foundational Systems, and Distributional Reinforcement Learning
Related skills
llms reinforcement learning lmms bayesian learning bayesian neural networks📋 Description
- Lead research and development of Bayesian and distributional RL systems.
- Integrate LLMs and LMMs with Bayesian frameworks for production.
- Design scalable AI systems that impact product and user experience.
- Collaborate with cross-functional teams to deploy production AI.
- Shape Airbnb's AI strategy and foundational intelligence fabric.
🎯 Requirements
- Bachelor's degree in CS, Mathematics, or related field.
- 15+ years in Applied ML, including production deployments.
- Proficiency in Python, Scala, Java, or C++ with TensorFlow/PyTorch.
- Experience with Bayesian Neural Networks, Bayesian Learning, and RL.
- Strong math: probability, statistics, optimization.
- Experience with Spark, Kafka, and distributed architectures.
- Knowledge of Mixture of Models, multitask learning, and sharded architectures.
🎁 Benefits
- US remote eligible.
- Occasional office visits may be required.
- Must live in a state where Airbnb has a registered entity.
- Reasonable accommodations available during recruitment.
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