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Artificial Intelligence (AI) Engineer / Developer (Remote)

Role overview

Qualifications

  • Bachelor’s or Master’s degree in Computer Science, Machine Learning, AI, Mathematics, or related fields
  • 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
  • Strong programming skills in Python; familiarity with Rust or other languages is a plus

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

Key facts

  • Remote from: United States
  • Fixed term
  • Mid-level (2-5 years)
  • AI Engineer
  • English

Hard skills

Other skills

  • Problem Solving
  • Communication
  • Collaboration

About the company

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Statheros

Company details

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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 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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MR

Marcus Rivera

Chief Revenue Officer

m.rivera@company.com
linkedin.com/in/marcusrivera
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