ML Engineer – Agent Training & Behaviour

Develop autonomous agents that learn, evolve, and adapt in real time. You’ll work on shaping agent behavior using RL, online learning, and model fine-tuning strategies that make AI smarter with every interaction.

Design agents that don’t just follow instructions—they learn, adapt, and improve autonomously in real-world scenarios.

Responsibilities

• Design and train ML models and reinforcement learning agents for real-world environments.
• Implement learning feedback loops and behavior tuning systems to evolve agent performance over time.
• Experiment with novel ways of reward modeling, simulation, and multi-agent interaction.
• Work in a cross-functional team alongside infra, product, and other ML engineers.

Requirements

• 3+ years in machine learning, with experience in agent-based modeling, reinforcement learning, or online learning.
• Strong Python skills and familiarity with frameworks like PyTorch, TensorFlow, Ray/RLlib.
• Interest in behavioral modeling, simulation environments, and scalable learning systems.

What we offer

• A significant role with the potential to shape the future of fintech and digital innovation
• The opportunity to work remotely, with flexible working hours and home office options
• Potential for relocation to our global offices
• Access to our mentoring program and the resources of the leading venture builder in the world

Hiring Process

1. Screening phone call with the recruiter
2. Interview with the hiring manager
3. Bootcamp: Showcase your skills with a real-life business challenge and meet the team

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