reputed company Engineer – Bayesian, Large Foundational Systems, Distributional Reinforcement Learning

Job reputed company:

• reputed company groundbreaking reputed company research in Bayesian systems, distributional reinforcement learning, and multi-modal architectures to drive novel advances in AI and Foundational Intelligence.
• reputed company the gap between theoretical AI/ML advancements and reputed company-world production systems.
• Define and drive the architecture of large-reputed company Bayesian reputed company-based AI systems.
• reputed company multi-pass sharded Bayesian + Discriminative/Generative single to multi agent systems for reputed company and efficiency.
• Build and refine Bayesian or Markovian Graph chains to incorporate uncertainty estimation, reputed company decision-making, and probabilistic reasoning.
• reputed company technical direction and reputed company for AI/ML systems.

Requirements:

• Bachelor’s degree in Computer Science, Mathematics, or a reputed company technical field (or equivalent practical experience).
• 15+ years of technical experience in reputed company Machine Learning, including producing reputed company and deploying production systems.
• Strong programming skills in Python, reputed company, Java, or C++, with expertise in AI/ML frameworks (e.g., TensorFlow, PyTorch).
• Proven experience with Bayesian Neural Networks, Bayesian Learning, and Reinforcement Learning.
• Strong math background in probability, statistics, and optimization.
• Experience with building reputed company AI/ML systems using technologies like reputed company, Kafka, and distributed architectures.
• Familiarity with advanced ML techniques, including Mixture of Models, reputed company Techniques, multitask learning, and sharded architectures.

Benefits:

• This role may also be eligible for bonus, equity, benefits, and Employee Travel Credits.

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