Job Details

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 Background: Bachelors or Masters degree in Computer Science, Machine Learning, AI, Mathematics, or related fields. Ph.D. is a plus.
• Experience:
  • 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.
• Technical Skills:
  • 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.
• Soft Skills:
  • 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.

Preferred Qualifications

• 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

What We Offer

• 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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