The ideal candidate for this role is based in London or Amsterdam.

We are looking for a Machine Learning Software Engineer to help us improve our training algorithms, data pipeline and model architectures. Your work has a major impact on our roadmap of new AI features and your code will be shipped to a very large number of camera devices in the field. Together we are building the most advanced AI for embedded devices.

What you will be doing

• Our deep learning models are truly tiny - the memory footprint of our computer vision models is sometimes 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 and improve our large data warehouse that allows us to train our tiny deep learning models. Our automated data ingestion pipeline feeds unlabelled images to large auto labeling models, processes our large datasets (30 million images and videos), and generates datasets for model training.
• You will use our Kubernetes cluster to deploy TensorFlow training jobs, Weights & Biases to analyze results, Snowflake and Dataflow to build datasets, large multi-modal models for yet to be announced features, Streamlit to prototype new demos, and lots of GPUs on GCP for training new models and auto-labeling data.
• Our software is deployed in the field on a very large number of camera devices from major consumer brands. You will ship new features fast, use feedback from users to make our AI models ever more accurate, and make our API developer friendly. 
• We encourage you to take initiatives and take on many responsibilities. You will be part of a small team where everybody is expected to make a big impact on our products and the success of the company. Career advancement opportunities are likely as the company grows.

About Plumerai

Plumerai is making deep learning tiny and accurate. We make it easy for developers to add highly accurate AI to their embedded products and thereby enable them to create amazing new products. This is how we work towards a future with 100s of billions of intelligent sensors on the edge. Today, large customers deploy our People Detection, Familiar Face Identification, and ML inference engine software on their devices in the field. We will soon be offering many more libraries that enable our customers to use the most advanced AI inside their products. Making it possible to deploy AI on hardware that is cheap and low-power is the most effective way towards a future where AI helps all of us, without making any compromises on privacy.

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, pre- and postprocessing, and all the way down to the fastest inference engines. If you want to learn more, have a look at some of our talks, our open-source deep learning library Larq and our published research (NeurIPS, MLSys, MLPerf).

Our team is based in London and Amsterdam and we are backed by world-class investors including Tony Fadell (creator of iPod, iPhone, founder of Nest), Hermann Hauser (founder of Arm) and Zoubin Ghahramani (University of Cambridge, Google DeepMind).

Requirements

What You Need

• Strong software engineering skills and proficiency in Python.

• Very comfortable with frameworks such as TensorFlow and Keras (which we use),  PyTorch or JAX.

Nice To Have

• Industry experience with object detection and other computer vision tasks.
• Experience with training neural networks that moved into production.
• Ability to build maintainable infrastructure using tools such as Docker/Kubernetes. You are eager to work with Snowflake, Apache-Beam and GCP.

We value a proven track record of building things and working with large-scale software projects, either as a professional or through open-source contributions. We look for people that are eager to learn about all parts of the company's success and who can teach themselves new technologies along the way.

Benefits

What we offer:

• Stock options.
• Competitive salary.
• 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 and CVPR.

We have flexible working hours and like to work together from our offices in London and Amsterdam on at least 2 fixed days per week, but visiting the office more often is also possible.