Artificial Intelligence (AI) Engineer / Developer (Remote)

Statheros

  • San Antonio, Texas
  • 30+ days ago
  • Remote

    Highlights

    Statheros is a small DEFTECH firm focused on developing cutting-edge AI and autonomy systems for the US Department of Defense. Develop and train reinforcement learning models for real-world applications, focusing on efficiency and scalability.

    Numbers & Facts

    LocationSan Antonio, Texas (
    Remote
    )

    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 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: Bachelor’s or Master’s 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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