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# Deep Learning Research Engineer

- **Company:** Plumerai
- **Location:** Amsterdam, Netherlands
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Artificial Neural Networks, Computer Vision, Data Flow Control, Python (Programming Language), Tensorflow, Reinforcement Learning, Graphics Processing Unit (GPU), Pytorch, Large Language Models, Snowflake, Deep Learning, Keras, Kubernetes, Streamlit Framework, Data Pipelines
- **Published:** July 15, 2026
- **Apply:** https://www.adzuna.nl/details/5721070399

## About the Role

* Strong engineering experience with proficiency in Python.
 * Comfortable with frameworks such as PyTorch, TensorFlow, Keras, or JAX.
 * Strong experience with computer vision and multimodal LLMs.
 * Trained neural networks that moved into production.

Nice To Have

 * Industry experience with efficient inference deployments (cloud or edge).
 * Experience with Deep Reinforcement Learning.

We only consider applicants who are currently based in, or willing to relocate to, London or Amsterdam. We have flexible working hours and work together from our offices on at least 2 fixed days per week.

## Description

We are looking for a Deep Learning Research Engineer that can help us develop state of the art AI products. This can involve anything from improving our training algorithms, training and integrating multimodal LLMs, building our data pipeline, designing new model architectures to using tried and tested ML approaches and coming up with clever algorithms. You will help us build new AI features that will be shipped to millions of camera devices in the field. Together we are building the most advanced AI for embedded devices.

What you will be doing

 * We combine our Tiny AI with multimodal LLMs to enable our advanced AI features for our customers. You will use and improve multimodal LLMs to achieve new functionality for our customers and optimize their deployments (cloud and edge).
 * Some of our deep learning models are truly tiny - the memory footprint of our smallest computer vision model is just 1MB. You will train and design more accurate models, while also enabling new and more complex AI applications on low-cost and low-power hardware.
 * You will improve our data pipeline, model architectures and training software. Sometimes there is relevant literature available, but novel approaches and clever hacks are often required for the problems that we are working on.
 * You will use our Kubernetes cluster to deploy PyTorch and TensorFlow training jobs, Snowflake and Dataflow to build datasets, tools like Streamlit to prototype new demos (try one of our live demos here) and lots of GPUs on GCP for training new models and auto-labeling data.


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