
2 - 10 employees
Statheros is like Bitcoin, but without the volatile price changes. It has its value backed by real estate, meaning its value will remain more stable than gold over time.
🔥 1 hour ago
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2 - 10 employees
Statheros is like Bitcoin, but without the volatile price changes. It has its value backed by real estate, meaning its value will remain more stable than gold over time.
• Design, implement, and optimize Proximal Policy Optimization (PPO) algorithms for domain-specific use cases. • Develop and train reinforcement learning models for real-world applications, focusing on efficiency and scalability. • Collaborate with cross-functional teams to integrate PPO models into production systems. • Analyze model performance and experiment with hyperparameter tuning to achieve optimal results. • Stay up-to-date with the latest research and advancements in reinforcement learning and apply them to enhance existing solutions. • Build robust pipelines for training, evaluation, and deployment of RL models. • Document workflows, methodologies, and code for reproducibility and knowledge sharing.
• Bachelor’s or Master’s degree in Computer Science, Machine Learning, AI, Mathematics, or related fields. • 4+ years of professional experience in machine learning, with a focus on reinforcement learning. • Demonstrated expertise in implementing and optimizing PPO or similar reinforcement learning algorithms. • Hands-on experience with frameworks like TensorFlow, PyTorch, or JAX. • Strong programming skills in Python; familiarity with Rust or other languages is a plus. • Proficiency in designing and running RL experiments in simulated or real-world environments. • Experience with distributed training systems for reinforcement learning. • Solid understanding of policy gradient methods and reinforcement learning theory. • Excellent problem-solving skills and the ability to work in a collaborative, fast-paced environment. • Strong communication skills for presenting findings and collaborating with interdisciplinary teams.
• Remote work location. • Competitive salary. • Flexible work schedule. • Opportunities for professional development and research contributions. • Access to state-of-the-art resources and tools for AI development. • The chance to work on groundbreaking projects with a talented and passionate team.
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🇺🇸 United States – Remote
💰 Non Equity Assistance on 2024-03
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