Job Description
About Us
Statheros is a small DEFTECH firm focused on developing cutting-edge AI and autonomy systems for the US Department of Defense. Our passionate team builds intelligent systems to solve complex problems. We are seeking a talented AI Engineer specializing in Proximal Policy Optimization (PPO) to lead AI-enabled algorithm development for automating air traffic radar systems.
Job Responsibilities
- Design, implement, and optimize PPO algorithms for specific use cases.
- Develop and train reinforcement learning (RL) models prioritizing efficiency and scalability.
- Collaborate with cross-functional teams to integrate PPO models into production systems.
- Analyze model performance and perform hyperparameter tuning.
- Stay current with advances in reinforcement learning to improve solutions.
- Build pipelines for training, evaluation, and deployment of RL models.
- Document workflows, methodologies, and code for reproducibility.
Qualifications
- Educational Background: Bachelor’s or Master’s in Computer Science, Machine Learning, AI, Mathematics, or related fields; Ph.D. is a plus.
- Experience:
- 4+ years in machine learning, especially reinforcement learning.
- Proven expertise in PPO or similar algorithms.
- Hands-on with frameworks like TensorFlow, PyTorch, or JAX.
- Technical Skills:
- Strong Python programming; familiarity with Rust or others is a plus.
- Experience with RL experiments in simulations or real environments.
- Experience with distributed RL training systems.
- Understanding of policy gradient methods and RL theory.
- Soft Skills:
- Excellent problem-solving abilities.
- Strong communication skills for team collaboration.
Preferred Qualifications
- Applying PPO to domains like robotics, gaming, or finance.
- Familiarity with tools like OpenAI Gym, RLlib.
- Knowledge of parallel computing and GPU acceleration.
What We Offer
- Remote work opportunity.
- Competitive salary.
- Flexible schedule.
- Opportunities for professional growth.
- Access to cutting-edge AI resources.
- Engage in groundbreaking projects with a passionate team.
Job Highlights
Qualifications
- BSc/MSc in relevant fields.
- 4+ years in ML and reinforcement learning.
- PPO algorithm expertise.
- Experience with TensorFlow, PyTorch, or JAX.
- Proficiency in RL experiments.
- Experience with distributed RL training.
- Knowledge of policy gradients and RL theory.
- Strong problem-solving and communication skills.
Benefits
- Remote work.
- Competitive salary.
- Flexible work hours.
- Professional development.
- Advanced AI tools.
- Impactful projects.
Responsibilities
- Develop PPO algorithms.
- Train RL models for real-world applications.
- Collaborate for integration into production.
- Optimize model performance.
- Keep updated with RL research.
- Build training, evaluation, and deployment pipelines.
- Document processes and code.