AI Research Engineer

At Plumerai, we make it easy and affordable for developers to add highly accurate AI to their embedded devices and thereby enable them to create amazing new products. We combine our on-device Tiny AI software with our cloud-based multimodal LLMs, providing People Detection, Video Search, Familiar Face Identification, AI Captions and more.

Major enterprises deploy our advanced computer vision models on millions of smart home cameras in the field and we’re rapidly expanding into commercial security, retail, assisted living, and more. The best solution runs as much as possible on-device to enable low-power, accurate, and private AI products. This is where Plumerai leads, demonstrating better accuracy even than Google Nest. We are now starting to invest heavily in market adoption.

We build the most accurate and efficient AI solutions by vertically integrating all layers of the stack. From data collection and curation, custom training software, model architectures, multimodal LLMs, pre- and postprocessing, and all the way down to the fastest inference engines. Not only does our team have a deep theoretical understanding about all these components, we also know how to ship fast and often.

Our team is based in London and Amsterdam, we have recently raised funding to provide multiple years of runway, while our recurring revenue is growing rapidly. We are backed by world-class investors such as Tony Fadell, Hermann Hauser, Zoubin Ghahramani, and others.

We are looking for an AI 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.

• Use and improve multimodal LLMs to achieve new functionality for our customers and optimize their deployments (cloud and edge)
• Train and design more accurate models, while also enabling new and more complex AI applications on low-cost and low-power hardware
• Improve our data pipeline, model architectures and training software, applying novel approaches and clever hacks where needed
• Deploy training jobs on our Kubernetes cluster, use Snowflake and Dataflow to build datasets, prototype demos with Streamlit, and train new models on GCP GPUs for auto‑labeling data

• Very strong software engineering skills and proficiency in Python
• Comfortable with frameworks such as PyTorch, Tensor Flow, Keras, or JAX
• Strong experience with computer vision and multimodal LLMs
• Experience working in a team on the same software project

• Trained neural networks that moved into production
• Industry experience with efficient inference deployments (cloud or edge)
• Experience with Deep Reinforcement Learning

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

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.

Seniority level: Entry level

Employment type: Full-time

Job function: Information Technology

Industries: IT Services and IT Consulting