Applied Reinforcement Learning Researcher

Applied Reinforcement Learning Researcher

Job Description

Join Q’s CTO Research Team, where we push the boundaries of machine learning to build intelligent systems that interact, reason, and communicate like humans. We're looking for a visionary Applied Reinforcement Learning Researcher with hands-on experience in RL, RLHF, LLMs, NLP, speech recognition, and advanced reasoning systems.

This is not your average ML role — this is where bleeding-edge research meets proprietary data, practical implementation, and the opportunity to shape the future of how machines understand language and human behavior.

In this role you will bridge the gap between theory and practice to work closely with researchers, and engineers to design and develop SOTA reinforcement learning algorithms for human communication.

Requirements

• MSc or PhD in Computer Science, Engineering, or a related field.
• Hands-on experience in research, bonus if you’ve published papers
• Have explored reinforcement learning in theory and practice: training, tuning, experimenting, etc.
• Grounding in algorithms, data structures, and mathematical thinking.
• Fluent with machine learning, deep learning for time series, audio and video,.
• Can implement and build on research papers.
• Hands-on experience in pre-training, evaluating, fine-tuning and hyperparameter-tuning deep learning models at scale
• Love delivering tangible results — prototypes, demos, experiments.

​​Nice to have

• You’re up to date with arXiv and can explain the latest NeuroIPS, ICLR, or CVPR paper with a smile
• You love taking ownership and navigating ambiguity with creativity.
• You’re experienced in a research lab environment or a startup
• You bring positive energy to the table and enjoy learning with others.