Applied RL Engineer

Jobgether • United States

Remote

This Job is No Longer Active This position is no longer accepting applications

AI Summary

Design, develop, and deploy advanced reinforcement learning systems to solve complex decision-making challenges. Collaborate with technical teams to build scalable, reliable AI solutions where traditional ML approaches fall short. Requires deep expertise in RL theory, simulation, reward modeling, and production engineering.

Key Highlights

Design and deploy RL systems for complex operational and strategic challenges

Develop simulation environments and large-scale data collection pipelines

Train neural network policies using GPU clusters and scalable infrastructure

Optimize reward functions and ensure production-ready, safe RL systems

Key Responsibilities

Design, train, evaluate, and deploy reinforcement learning models for complex decision-making problems

Develop RL systems that move beyond traditional supervised learning approaches

Design and optimize reward functions for challenging environments

Build and maintain simulation environments and large-scale data collection pipelines

Train neural network-based policies using GPU clusters and scalable infrastructure

Evaluate model performance and support continuous policy optimization after deployment

Apply engineering best practices to ensure RL systems are stable, safe, and production-ready

Collaborate with research and engineering teams to translate AI concepts into practical solutions

Contribute technical insights through documentation, knowledge sharing, research publications, or open-source contributions

Interested in remote work opportunities in Development & Programming? Discover Development & Programming Remote Jobs featuring exclusive positions from top companies that offer flexible work arrangements.

Technical Skills Required

Python Reinforcement Learning Simulation Reward Modeling Deep Learning Frameworks

Benefits & Perks

Fully remote work within the United States

Competitive annual salary range of $100,000-$150,000

Opportunity to work on advanced AI and RL initiatives

Browse our curated collection of remote jobs across all categories and industries, featuring positions from top companies worldwide.

Nice to Have

Experience with RLHF for large language models

Familiarity with multi-agent reinforcement learning

Exposure to robotics, control systems, or autonomous systems

Contributions to open-source RL libraries or environments

Job Description

The Applied RL Engineer will design, develop, and deploy advanced reinforcement learning systems to solve complex decision-making challenges.This role combines cutting-edge research with practical engineering to bring RL solutions from experimentation into production environments.The position requires expertise in modern reinforcement learning techniques, simulation, reward modeling, and scalable model training.You will collaborate with technical teams to build reliable, high-impact AI systems where traditional machine learning approaches are not sufficient.The ideal candidate will have strong research foundations, engineering experience, and a passion for applying AI to real-world problems.

Want the full job description? Read the complete details on LinkedIn, the original posting.

Continue on LinkedIn

This is a short excerpt. All rights to the full description belong to its original publisher.