Deep Learning Research Engineer

The role

A Deep Learning Research Engineer will develop state of the art AI products. This involves improving training algorithms, integrating multimodal LLMs, and designing new model architectures for embedded devices.

What you will do

• Use and improve multimodal LLMs to achieve new functionality and optimize deployments.
• Train and design accurate models for low-cost and low-power hardware.
• Improve data pipeline, model architectures and training software.
• Deploy PyTorch and TensorFlow training jobs using a Kubernetes cluster.
• Build datasets using Snowflake and Dataflow.
• Prototype new demos using tools like Streamlit.
• Train new models and auto-label data using GPUs on GCP.

Required qualifications

• 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.
• Currently based in, or willing to relocate to, London or Amsterdam.

Nice to have

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

Benefits

• Competitive salary.
• Generous equity stake in the company.
• Relocation assistance.
• Visa sponsorship is provided.
• Choose your own laptop and equipment.
• 25 days of paid vacation time in addition to bank holidays.
• Ability to attend top research conferences like NeurIPS, ICML and CVPR.

Before you apply

• Applicants must be currently based in, or willing to relocate to, London or Amsterdam.
• Talent Screen
• Technical Round I
• Technical Round II
• Cross Team & Executive Interview

About the company

Plumerai makes it easy and affordable for developers to add highly accurate AI to camera devices. They combine on-device Tiny AI software with cloud-based Vision Language Models.