Deep Learning Research Engineer

At Plumerai, you'll work on advanced on-device AI for smart cameras, combining Tiny AI models with Vision Language Models. As a Deep Learning Research Engineer, you'll improve training algorithms, train and integrate multimodal LLMs, design model architectures, and build data pipelines for features deployed to millions of devices. This role involves solving novel ML problems and optimizing models for low-power, low-cost hardware.

• Use and improve multimodal LLMs to enable new customer functionality and optimize cloud/edge deployments.
• Train and design more accurate deep learning models for resource-constrained devices.
• Improve data pipelines, model architectures, and training software.
• Deploy PyTorch/TensorFlow training jobs on Kubernetes, build datasets with Snowflake/Dataflow, and prototype demos with Streamlit.

• Strong engineering experience with Python.
• Proficiency in PyTorch, TensorFlow, Keras, or JAX.
• Strong experience with computer vision and multimodal LLMs.
• Experience training neural networks that have moved into production.
• Based in or willing to relocate to London or Amsterdam.

• Industry experience with efficient inference deployments (cloud or edge).