About Us
Statheros is a small DEFTECH firm focused on developing cutting-edge AI and autonomy systems for the US Department of Defense. Our team is passionate about building intelligent systems that solve complex problems. We are looking for 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.
Job 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.
Qualifications
Educational BackgroundBachelor's or Master's degree in Computer Science, Machine Learning, AI, Mathematics, or related fields. Ph.D. is a plus.
Experience4+ 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.Technical SkillsStrong 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.Soft SkillsExcellent 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.Preferred Qualifications
Experience in applying PPO to [specific domain, e.g., robotics, gaming, finance, etc.]Familiarity with OpenAI Gym, RLlib, or other RL development environmentsKnowledge of parallel computing and GPU acceleration for large-scale RL tasksWhat We Offer
Remote work location.Competitive salary.Flexible work schedule.Opportunities for professional development and research contributionsAccess to state-of-the-art resources and tools for AI development.The chance to work on groundbreaking projects with a talented and passionate team.J-18808-Ljbffr