Reinforcement Learning Jobs in Seattle, WA (NOW HIRING)

Apply reinforcement learning concepts to solve complex behavioral and path planning challenges in simulation environments. * Identify and resolve "sim-to-sim" and "sim-to-real" fidelity gaps to ...

Apply reinforcement learning concepts to solve complex behavioral and path planning challenges in simulation environments. * Identify and resolve "sim-to-sim" and "sim-to-real" fidelity gaps to ...

NLP/NLU, LLMs, Reinforcement Learning, Human Feedback/HITL, Deep Learning, Speech Recognition, Conversational AI, Natural Language Modeling, Multimodal Learning. In this role, you will work alongside ...

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

... post-training, reinforcement learning, learning from execution feedback, search, and test-time scaling to improve performance on real-world tasks. - Build scalable agent infrastructure for ...

Apply reinforcement learning concepts to solve complex behavioral and path planning challenges in simulation environments. * Identify and resolve "sim-to-sim" and "sim-to-real" fidelity gaps to ...

... post-training, reinforcement learning, learning from execution feedback, search, and test-time scaling to improve performance on real-world tasks. - Build scalable agent infrastructure for ...

Experience with LLMs, reinforcement learning, imitation learning * Conference or journal publications in machine learning or robotics * Prior experience with agent behaviors, prediction, autonomous ...

We employ techniques from GenAI/LLMs, supervised/semi-supervised learning, deep learning, transformer architectures, using outcomes from causal Econometric modeling, and Reinforcement learning. As ...

We are building a self-healing ecosystem where Multi-Agent Systems and Reinforcement Learning (RL) loops work in tandem with Large Language Models (LLMs) to not only detect incidents in real-time but ...

We are building a self-healing ecosystem where Multi-Agent Systems and Reinforcement Learning (RL) loops work in tandem with Large Language Models (LLMs) to not only detect incidents in real-time but ...

The Search WPPO Science team is responsible for developing large-scale machine learning systems-spanning ranking, reinforcement learning, and large language models (LLMs)-that power the next ...

We employ techniques from GenAI/LLMs, supervised/semi-supervised learning, deep learning, transformer architectures, using outcomes from causal Econometric modeling, and Reinforcement learning. As ...

Develop and train end-to-end robot learning models, including vision-language-action (VLA) family of models, imitation learning policies, and reinforcement learning agents for manipulation ...

In this role, you'll work closely with a small, dynamic team of AI researchers and engineers exploring reinforcement learning, transformer-based architectures, and diffusion models. You'll be ...

Apply state-of-the-art LLM post-training techniques, such as instruction tuning, reinforcement learning from human feedback (RLHF), and continual learning, to optimize AI customer service responses ...

Your work may span AI agents, large language models, reinforcement learning, optimization, GPU-accelerated algorithms, verification, analog design, and other areas of chip design automation. This ...

Apply state-of-the-art LLM post-training techniques, such as instruction tuning, reinforcement learning from human feedback (RLHF), and continual learning, to optimize AI customer service responses ...

The Senior / Staff Machine Learning Research Scientist will conduct research on agent environments and reinforcement learning, guiding data strategy to innovate intelligent AI agents and contribute ...

Design and implement resource allocation and combinatorial optimization techniques (e.g., reinforcement learning, LLM agents for DSE, Bayesian optimization and other multi-objective optimization ...