{"id":3565626,"url":"https://alion.io/job/statheros-artificial-intelligence-ai-engineer-developer-remote","title":"Artificial Intelligence (AI) Engineer / Developer (Remote)","company":{"id":4391473,"name":"Statheros","domain":"statheros.tech","url":"https://alion.io/company/statheros-2","size_band":"11-50","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Freshteam","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"middle","employment_type":"contractor","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["United States"],"countries":["US"],"hiring_countries":["US"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":120000,"max_usd":238000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":85},"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Machine Learning","optional":false},{"name":"PPO","optional":false},{"name":"Reinforcement Learning","optional":false},{"name":"Reinforcement Learning","optional":false},{"name":"JAX","optional":true},{"name":"OpenAI","optional":true},{"name":"Python","optional":true},{"name":"PyTorch","optional":true},{"name":"Ray","optional":true},{"name":"RLlib","optional":true},{"name":"Rust","optional":true},{"name":"TensorFlow","optional":true}],"status":"live","first_seen_at":"2026-10-31T10:22:51Z","employer_posted_date":"2026-10-31","last_verified_at":"2026-11-03T07:53:58Z","board_verified":true,"closed_at":null,"days_open":2,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":2},"description":"About Us\nStatheros 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.\nJob Responsibilities\nDesign, implement, and optimize Proximal Policy Optimization (PPO) algorithms for domain-specific use cases.\nDevelop and train reinforcement learning models for real-world applications, focusing on efficiency and scalability.\nCollaborate with cross-functional teams to integrate PPO models into production systems.\nAnalyze model performance and experiment with hyperparameter tuning to achieve optimal results.\nStay up-to-date with the latest research and advancements in reinforcement learning and apply them to enhance existing solutions.\nBuild robust pipelines for training, evaluation, and deployment of RL models.\nDocument workflows, methodologies, and code for reproducibility and knowledge sharing.\nQualifications\nEducational Background: Bachelor’s or Master’s degree in Computer Science, Machine Learning, AI, Mathematics, or related fields. Ph.D. is a plus.\nExperience:4+ years of professional experience in machine learning, with a focus on reinforcement learning.\nDemonstrated expertise in implementing and optimizing PPO or similar reinforcement learning algorithms.\nHands-on experience with frameworks like TensorFlow, PyTorch, or JAX.\n\nTechnical Skills:Strong programming skills in Python; familiarity with Rust or other languages is a plus.\nProficiency in designing and running RL experiments in simulated or real-world environments.\nExperience with distributed training systems for reinforcement learning.\nSolid understanding of policy gradient methods and reinforcement learning theory.\n\n Soft Skills:Excellent problem-solving skills and the ability to work in a collaborative, fast-paced environment.\nStrong communication skills for presenting findings and collaborating with interdisciplinary teams.\n\nPreferred Qualifications\nExperience in applying PPO to [specific domain, e.g., robotics, gaming, finance, etc.]\nFamiliarity with OpenAI Gym, RLlib, or other RL development environments\nKnowledge of parallel computing and GPU acceleration for large-scale RL tasks\nWhat We Offer\nRemote work location.\nCompetitive salary.\nFlexible work schedule.\nOpportunities for professional development and research contributions\nAccess to state-of-the-art resources and tools for AI development.\nThe chance to work on groundbreaking projects with a talented and passionate team.","description_format":"text","description_chars":2726,"description_truncated":false,"requirements":{"experience_years_min":4,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":["Flexible schedule","Professional development"],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Artificial 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