Who We Are:

We build the intelligence that lets robots sense, reason, and act in the real world—moving beyond the lab and into everyday industrial settings like warehouses and factories. Our technology closes the automation gaps that traditional systems can’t solve. We are on a mission to redefine how physical work gets done, and we’re looking for curious, bold thinkers to help shape the future of robotics with us.

Overview:

As an Imitation Learning Researcher, you will work on developing and improving state-of-the-art imitation learning algorithms and methodologies. You’ll design experiments, create datasets, and develop models that enable systems to mimic human decision-making processes in real-world applications. This role involves close collaboration with cross-disciplinary teams to integrate findings into practical applications.

Your Responsibilities:

Design

Design and implement advanced imitation learning algorithms.
Develop, test, and deploy models in Python/C++/TensorRT/GGUF.

Optimize

Analyze and preprocess datasets for training models.
Conduct experiments to evaluate model performance and improve robustness.
Collaborate with other researchers and engineers to integrate solutions into larger systems.

Qualifications:

Education and Experience

Master’s or Ph.D. in Computer Science, Machine Learning, Robotics, or a related field.

Skills

Strong proficiency in Python and PyTorch.
Strong understanding of machine learning principles, particularly reinforcement, imitation learning, behaviour cloning, generative AI (e.g. Diffusion, Flow Matching, VAEs).
Familiarity with teleoperation, ROS2 framework and open-source platforms such as HuggingFace, Detectron2.
Strong ability to customize algorithm for different use-cases and multi-modality fusion.
Strong analytical and problem-solving skills

What We Offer:

Wellpass (gym membership)
Flexible working hours
Option to work from home when needed
A motivated team and an open corporate culture
Competitive compensation and excellent career development opportunities

Note to applicants: We are currently experiencing a high volume of interest in this role. Due to this, our review process is taking a bit longer than usual. We appreciate your patience.

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