Reinforcement Learning Engineer (AI)

Location: 100% remote within the United States

Salary: $100,000–$150,000 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 and implement reinforcement learning solutions for sequential decision-making in real and simulated environments.
• Develop, calibrate, and maintain simulation environments and large-scale experience collection systems.
• Implement and evaluate policy gradient, actor-critic, off-policy, offline RL, imitation learning, RLHF, and DPO techniques.
• Engineer reward functions, safety constraints, conservative policies, and human-in-the-loop oversight mechanisms.
• Build scalable distributed RL training infrastructure, optimize training stability and sample efficiency, and monitor production policies for drift and regressions.
• Collaborate with applied scientists and product teams, document technical decisions, and translate RL research into production-ready solutions.

Requirements

• Master’s or PhD in Computer Science, Machine Learning, or a related field, or equivalent applied experience.
• 10+ years of combined reinforcement learning research and engineering experience.
• Strong proficiency in Python and modern deep learning frameworks.
• Experience with a major RL library or in-house RL stack, reward-function design, simulation environments, and large-scale experience collection.
• Experience training neural network policies on GPU clusters and a strong foundation in probability, optimization, and reinforcement learning theory.
• Must be eligible to work in the United States as a U.S. citizen, Green Card holder, EAD holder, or H-1B transfer candidate; new H-1B sponsorship is not available.

Nice to have

• RLHF experience for large language models.
• Multi-agent RL or hierarchical RL experience.
• Exposure to robotics, control systems, or autonomous driving.
• Publications in RL or related research venues.
• Open-source contributions to RL libraries or environments.

Culture & Benefits

• Fully remote work within the United States.
• Direct W2 employment.
• Career growth opportunities within an established consulting and software development organization.
• Work with applied scientists and product teams on cloud, AI, data, and enterprise solutions.