Artificial Intelligence (AI) Engineer / Developer (Remote)

Summary

Statheros is a small DEFTECH firm focused on developing cutting-edge AI and autonomy systems for the US Department of Defense. They are seeking a talented AI Engineer specializing in Proximal Policy Optimization (PPO) to lead the development of AI-enabled algorithms that automate the operation of air traffic radar systems.

Responsibilities

• 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

Skills

• Bachelor's or Master's degree in Computer Science, Machine Learning, AI, Mathematics, or related fields. Ph.D. is a plus
• 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
• Experience in applying PPO to [specific domain, e.g., robotics, gaming, finance, etc.]
• Familiarity with OpenAI Gym, RLlib, or other RL development environments
• Knowledge of parallel computing and GPU acceleration for large-scale RL tasks

Qualifications

Must Haves

• Bachelor's or Master's degree in Computer Science, Machine Learning, AI, Mathematics, or related fields. Ph.D. is a plus
• 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

Nice to Haves

• Experience in applying PPO to [specific domain, e.g., robotics, gaming, finance, etc.]
• Familiarity with OpenAI Gym, RLlib, or other RL development environments
• Knowledge of parallel computing and GPU acceleration for large-scale RL tasks

Benefits

• 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.