Bayesian Modeling Jobs in California (NOW HIRING)

AI Foundations areas that we are currently focusing on include reinforcement learning, learning from demonstration, generative modeling, Bayesian inference, hierarchical learning, and robust ...

Proficiency across multiple ML domains: supervised and unsupervised learning, deep learning, time-series modeling, and Bayesian statistics. Production-quality software engineering in Python ...

Responsibilities : • Training machine learning models over billions of data points. • Quantifying predictive uncertainty using probabilistic and Bayesian methods. • Creating models that quickly ...

Apply your expertise in designing, implementing and validating unsupervised deep learning, reinforcement learning and bayesian models. * Present exploratory findings to both, technical and management ...

Familiarity with Bayesian inference, management of structural and parametric uncertainty and variability, in complex dynamic models. * Experience with AI-assisted coding (vibe coding) and skill ...

Experience with simulation systems, probabilistic modeling, Bayesian methods, survival analysis, causal impact modeling, reinforcement learning concepts, or uncertainty quantification Experience ...

Experience with simulation systems, probabilistic modeling, Bayesian methods, survival analysis, causal impact modeling, reinforcement learning concepts, or uncertainty quantification Experience ...

Apply your expertise in designing, implementing and validating unsupervised deep learning, reinforcement learning and bayesian models. * Present exploratory findings to both, technical and management ...

Develop highly scalable deep learning, reinforcement learning and bayesian models. * Support research projects by providing innovative designs for end-to-end Machine Learning systems. * Optimize ...

Develop highly scalable deep learning, reinforcement learning and bayesian models. * Support research projects by providing innovative designs for end-to-end Machine Learning systems. * Optimize ...

Conducting binary and categorical and binary data analyses, time-to-event (hazard) models, Poisson models, MCMC and Bayesian methods as applied to exposure-response analyses and Population PK and ...

Conducting binary and categorical and binary data analyses, time-to-event (hazard) models, Poisson models, MCMC and Bayesian methods as applied to exposure-response analyses and Population PK and ...

In this role you will be building and deploying machine learning models using both analytical ... Bayesian Learning, Reinforcement Learning, or Deep Learning) to real-world problems and datasets.

Conducting binary and categorical and binary data analyses, time-to-event (hazard) models, Poisson models, MCMC and Bayesian methods as applied to exposure-response analyses and Population PK and ...

In this role you will be building and deploying machine learning models using both analytical ... Bayesian Learning, Reinforcement Learning, or Deep Learning) to real-world problems and datasets.

Lead technical work of a Scrum team: initiating and designing model solutions, driving ... Bayesian learning, reinforcement learning, or deep learning) to real‑world problems and datasets.

Collaborates with stakeholders to define success criteria and align model metrics with business ... Bayesian Learning, Reinforcement Learning, or Deep Learning) to real-world problems and datasets.

In this role you will be building and deploying machine learning models using both analytical ... Bayesian Learning, Reinforcement Learning, or Deep Learning) to real-world problems and datasets.

Collaborates with stakeholders to define success criteria and align model metrics with business ... Bayesian Learning, Reinforcement Learning, or Deep Learning) to real-world problems and datasets.

In this role you will be building and deploying machine learning models using both analytical ... Bayesian Learning, Reinforcement Learning, or Deep Learning) to real-world problems and datasets.