VLA Engineer
- Training policies using representation learning, behaviour cloning, and reinforcement learning—taking models from data to deployment.
- Building pipelines that fuse vision, language, audio, proprioception, and 3D data into unified learning systems.
- Scaling distributed training frameworks and optimising models for real-time edge inference.
- Helping shape the way intelligent systems learn and act in the real world.
- 3+ years’ experience developing deep learning systems, with shipped models or published research.
- Hands-on expertise with Vision-Language Models (VLMs), LLMs, or generative models.
- Strong skills in Python + PyTorch or JAX (debugging, profiling, shipping).
- Passion for bridging the gap between simulation and real-world deployment.
- Previous experience in autonomous vehicle or machinery systems is highly desirable.
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