AI Innovator
3 days ago
Cubiq Recruitment is partnering with a dynamic AI/DataOps startup to find exceptional Reinforcement Learning Engineers. As a pre-Series A company, they are poised for significant growth, tackling industry challenges through cutting-edge computer vision and AI solutions.
About the Role
This is an exciting opportunity for a seasoned RL Engineer with a solid background in computer vision, data management, and AI-driven modelling. You will design and deploy pioneering RL algorithms that are not just theoretical but engineered for real-world applications. Your key responsibilities will include algorithm development, data management, model training and optimisation, simulation and deployment, and collaboration.
Key Responsibilities:
- Algorithm Development: Design and implement advanced RL algorithms, covering model-based and model-free approaches (e.g., Q-learning, DQN, Policy Gradient, Actor-Critic).
- Data Management: Oversee data preparation and integrity to support robust model training.
- Model Training and Optimisation: Train, fine-tune, and optimise RL models, ensuring scalability and performance.
- Simulation and Deployment: Design simulation environments for effective model training and deploy RL models in production for real-world impact.
- Collaboration: Work cross-functionally to align AI solutions with business needs and communicate technical results to non-technical stakeholders.
What We Offer
A competitive salary of £90,000 - £110,000 per annum, plus benefits package. You will be part of a high-growth startup backed by one of the world's leading companies, ensuring stability while driving innovation. Our supportive, agile work environment encourages professional growth, and we offer flexibility with remote and hybrid work options across the UK and Europe.
Requirements
Experience: 4+ years in RL development with both model-based and model-free techniques. Technical Skills: Proficiency in Python, strong understanding of RL concepts, and familiarity with tools like OpenAI Gym, Stable Baselines, and RLLib. Education: Bachelors in Computer Science or similar, with preference for Masters/Ph.D. in ML or AI.
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