Artificial Intelligence (AI) Engineer / Developer (Remote)

Statheros; Huntsville (AL); Remote; USD 80,000 - 120,000; Full time

Job summary

An innovative DEFTECH firm is seeking a talented AI Engineer specializing in Proximal Policy Optimization (PPO) to lead the development of cutting-edge AI algorithms for air traffic radar systems. This role offers the opportunity to work on groundbreaking projects that enhance operational efficiency and safety. You will design and optimize reinforcement learning models while collaborating with cross-functional teams to integrate these solutions into real-world applications. Join a passionate team dedicated to pushing the boundaries of AI technology and making significant contributions to the defense sector. If you thrive in a dynamic environment and are eager to tackle complex challenges, this is the perfect opportunity for you.

Benefits

Competitive salary

Flexible work schedule

Opportunities for professional development

Access to state-of-the-art resources

Work on groundbreaking projects

Qualifications

• 4+ years of experience in machine learning with a focus on reinforcement learning.
• Expertise in implementing and optimizing PPO algorithms.

Responsibilities

• Design and optimize PPO algorithms for air traffic radar systems.
• Collaborate with teams to integrate models into production systems.

Skills

Proximal Policy Optimization (PPO)

Reinforcement Learning

Python Programming

TensorFlow

PyTorch

JAX

Rust

Distributed Training Systems

Policy Gradient Methods

Education

Bachelor’s degree in Computer Science

Master’s degree in AI or related fields

Ph.D. in relevant fields

Tools

OpenAI Gym

RLlib

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.