Reinforcement Learning Engineer

DataRoot Labs is a full-cycle AI R&D center—and Ukraine’s largest hub of AI talent and compute. Over the past 10+ years, we’ve shipped 45+ AI-powered products for leaders and startups across Automotive, Energy, Navigation, Gaming, Education, and more
 

Our client builds autonomous yard trucks that replace human drivers to make logistics yards safer, faster, and more efficient
 

Your mission: make the AI stack see in 3D and drive correctly—every time

Responsibilities:

• Research and develop advanced reinforcement learning (RL) algorithms and their applications
• Build, simulate, and test RL environments for real-world deployment scenarios
• Apply modern deep learning techniques, including transformers and computer vision, to RL problems
• Optimize inference performance for large-scale RL solutions

Requirements:

• Have a strong background in Reinforcement Learning and Deep Learning
• Hands-on experience with simulation and environments for RL
• Proven production experience in RL, including deployment cases
• Deep understanding of RL techniques (e.g., policy gradients, actor-critic, Q-learning)
• Experience with transformers and computer vision
• Upper-Intermediate English (written & spoken) for documentation and collaboration
• Strong knowledge of Python
• Experience with inference optimization

Would be a plus:

• Experience with Vision-Language Architectures (VLAs)
• Work with edge devices and sensors (e.g., camera, lidar, radar, etc.)
• Experience in automotive or robotics
• Knowledge of C++/CUDA

What We Offer:

• Real autonomy impact. Work on vehicles that use RL, Vision-Language-Action (VLA) and many other latest architectures
• Access to DGX H200 systems and large-scale GPU clusters
• Startup pace, research mindset, and a goal-oriented team
• Newest technical equipment and modern MLOps
• 20 working days of paid vacation, English courses, educational events & conferences, and medical insurance
• Your engineering will directly influence how autonomous vehicles perceive and act