Deep Learning Research Engineer

Stack

Responsibilities

• ▹Use and improve multimodal LLMs to deliver new customer functionality and optimize cloud and edge deployments
• ▹Train and design more accurate models while enabling more complex AI applications on low-cost, low-power hardware
• ▹Improve the data pipeline, model architectures and training software
• ▹Deploy PyTorch and TensorFlow training jobs on a Kubernetes cluster
• ▹Build datasets with Snowflake and Dataflow and prototype demos with Streamlit
• ▹Use GPUs on GCP to train new models and auto-label data

Requirements

• ▹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

What we offer

• ▹Competitive salary
• ▹Generous equity stake in the company
• ▹Relocation assistance and visa sponsorship
• ▹Choose your own laptop and equipment
• ▹25 days of paid vacation in addition to bank holidays
• ▹Ability to attend top research conferences (NeurIPS, ICML, CVPR)
• ▹Flexible working hours, with at least 2 fixed office days per week

About the company

Plumerai makes it easy and affordable for developers to add accurate AI to camera devices. Its models run on millions of smart home cameras, and the small team based in London and Amsterdam plans to double in size after its $8.7M Series A.