Reinforcement Learning Jobs in Kentucky (NOW HIRING)

Adjust frameworks and interfaces to accelerate machine learning development * Derive practical solutions and integrate them with the results of other teams to provide the best overall resolution ...

About the RL Teams Our Reinforcement Learning teams lead Anthropic's reinforcement learning research and development, playing a critical role in advancing our AI systems. We've contributed to all ...

You will work on problems involving reinforcement learning, model evaluations, language models, multimodal systems, and classifiers, taking ambiguous technical questions and turning them into ...

This role sits at the intersection of agentic AI and reinforcement learning, where your research will directly shape how enterprises leverage intelligent automation. AS AN AI RESEARCH SCIENTIST AT ...

Deep understanding of reinforcement learning, imitation learning, and optimization for dynamic systems * Strong programming skills (C++/Rust, Python) * Strong data analysis skills * Experience with ...

LLMs and Multi-Modal Foundation Models, LLM Reasoning, Reinforcement Learning, Agentic AI and others.* Provide technical leadership in research and applied projects and guide research directions to ...

The role requires hands-on experience with various reinforcement learning methods and a deep understanding of decision-making frameworks. Qualifications : Required : • 3+ years building and ...

We work across the full model stack--pretraining, midtraining, reinforcement learning, post‑training, evaluations, harnessing, and deployment--and connect that research to the patients, clinicians ...

We work across the full model stack--pretraining, midtraining, reinforcement learning, post‑training, evaluations, harnessing, and deployment--and connect that research to the patients, clinicians ...

Reinforcement learning integration -- Partner with data science teams to operationalize reinforcement learning and decision optimization models within NBA workflows, ensuring recommendations can be ...

Train policies using imitation learning, reinforcement learning, diffusion policies, and human demonstrations * Adapt and deploy VLA and robotics foundation models on physical humanoids * Build ...

... reinforcement learning, and system optimization, advancing recommendation systems beyond click ... prediction toward general-purpose recommendation agents.We believe the future of recommendation is ...

Explore and prototype advanced ML techniques (e.g., reinforcement learning, sequence modeling, transformers) where they can provide clear business value. Statistics, Experimentation & Model Design

The role will apply advanced statistical methodologies, machine learning, reinforcement learning, generative AI, and emerging analytical techniques while partnering with data engineers, AI/ML ...

Optimize agent behavior through feedback loops, reinforcement learning, or user interaction. * Engineer and manage context for agents to ensure they access the right information at the right time.

... reinforcement learning. 3+ years of experience covering machine learning workflows, data sampling and curation, pre‑processing, model training, ablation studies, evaluation, deployment, and ...

Reinforcement learning post-training is driving some of the most significant capability gains in AI today. It is the process that teaches a model to reason through hard problems, follow complex ...

Develop the infrastructure, parallelization, and APIs that power reinforcement learning agents and routing algorithms at massive compute scale. * Physics Team: Implement geometry checks and physics ...

Experience with model predictive control, optimal control, or reinforcement learning (sequential decision-making) * Experience working from raw logs or sensor data -- comfortable building analysis ...

We sit between the rendering algorithms team and everyone who consumes simulated sensor data -- perception training, closed-loop validation and reinforcement learning. We care about determinism ...