ML Engineer

We are looking for an ML Engineer to join our research team — someone passionate about building and deploying intelligent agents in complex environments.

This role is ideal for someone who wants to grow in a highly technical environment, learn from an experienced team, and make an impact on real-world systems.

Responsibilities:

• Developing RL agents in dynamic environments: implementing and tuning models to achieve high performance;
• Analyzing and optimizing training: evaluating agent behavior, refining training logic and hyperparameters based on results;
• Validating and selecting agents: designing testing and comparison pipelines to filter the best agents and checkpoints for deployment;
• Production integration and monitoring: deploying agents, analyzing real-world performance, and iteratively improving models and decision logic;
• Automating RL workflows: building and maintaining pipelines to streamline and accelerate the entire lifecycle.

Requirements:

• Proficient in Python (NumPy, pandas) and RL libraries (Stable Baselines3, RLlib, SKRL);
• Hands-on experience with RL algorithms;
• Strong understanding of classical ML – gradient boosting, clustering, and other methods;
• Practical experience with PyTorch, JAX, or TensorFlow;
• Research Implementation – сapability to read papers, reproduce and adapt algorithms, run ablations, and validate hypotheses experimentally:
• Strong algorithmic thinking – LeetCode-level proficiency is a big plus;
• Clear, structured communication – you know how to listen, learn, and articulate your ideas effectively.

Will be a plus::

• Experience with Isaac Gym/Sim/Lab or similar simulators (PyBullet, MuJoCo, Unity ML-Agents);
• Deep learning practice – solid understanding of CNNs, LSTMs, Transformers, and the ability to apply them effectively.

We offer:

• Flexible schedule - you choose when to start your day;
• Relocation to Bilbao, Spain for you and your family, with full support at every stage (documents, housing, adaptation, even pets);
• Unlimited vacation - take time off when you really need it;
• A culture of trust and respect for professionals, with no micromanagement;
• A modern office in a cozy district, regular team events and off-sites;
• Growth and participation in architectural decisions, challenging tasks, and a strong team you can learn from.