Autonomous Learning Engineer (AI)

Location: 100% remote within the United States

Salary: $130,000–$180,000 annually

Company

hirify.global is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States.

What you will do

• Design, develop, and deploy reinforcement learning solutions for complex decision-making and autonomous systems.
• Architect scalable training pipelines using distributed computing and GPU-accelerated infrastructure.
• Build and optimize simulation environments for training and validating reinforcement learning agents.
• Develop and evaluate RL algorithms, reward models, policy optimization techniques, RLHF, imitation learning, offline reinforcement learning, and multi-agent learning systems.
• Improve model convergence, sample efficiency, training stability, inference performance, reliability, safety, monitoring, and production scalability.
• Collaborate with AI researchers, data scientists, software engineers, and product teams while mentoring engineers and providing technical leadership.

Requirements

• 10+ years of professional experience in artificial intelligence, machine learning, deep learning, or reinforcement learning.
• Bachelor’s or Master’s degree in computer science, artificial intelligence, machine learning, robotics, mathematics, or a related technical discipline.
• Expert Python skills and extensive experience with PyTorch, TensorFlow, or JAX.
• Experience with Ray RLlib, Stable-Baselines3, CleanRL, or Acme, as well as simulation tools such as Gymnasium/OpenAI Gym, Isaac Sim, MuJoCo, Unity ML-Agents, or NVIDIA Omniverse.
• Experience with distributed training, GPU acceleration, model optimization, large-scale AI infrastructure, and deployment on AWS, Microsoft Azure, or Google Cloud Platform.
• Applicants must be U.S. citizens, Green Card holders, EAD holders, or eligible for H-1B transfer. New H-1B visa petitions cannot be sponsored.

Nice to have

• Experience with RLHF, multi-agent reinforcement learning, robotics, autonomous systems, control systems, foundation models, LLM alignment, or agentic AI.
• Experience with MLOps, Kubernetes, Docker, CI/CD pipelines, and production AI deployment.
• AI research publications, open-source contributions, patents, or recognized technical leadership in reinforcement learning.
• Knowledge of responsible AI, AI safety, model governance, explainability, and regulatory compliance.
• Ph.D. or specialized Master’s degree in artificial intelligence, machine learning, reinforcement learning, robotics, or control systems.

Culture & Benefits

• Full-time direct W-2 employment.
• Fully remote work within the United States.
• Opportunity to work on enterprise-scale cloud, AI, data, and software solutions.
• Career growth opportunities within an established technology consulting organization.