A fast growing Healthtech startup are on a mission to understand and structure the world’s medical data.
With current funding, they are looking to add a Machine Learning Engineer to join the team, ideally, someone who can not only design machine-based systems but also think creatively about the human interactions necessary to augment and train those systems.
In the role you will:
- Develop NLP systems that help us structure and understand biomedical information
- Work with a range of structured and unstructured data sources
- Design and build customized, large-scale cloud-based machine learning systems
- Design innovative data-acquisition and labelling systems, leveraging tools & techniques like crowdsourcing and novel active learning approaches
- Industry or academic experience working on a range of ML problems, particularly NLP
- Expert software development skills with a focus for building sound and scalable ML.
- Excitement about taking cutting-edge technologies and techniques to one of the most important and most archaic industries.
- A passion for finding, analyzing, and incorporating the latest research directly into the production environment.
- Good intuition for understanding what good research looks like, and where we should focus effort to maximize outcomes
Bonus points if you have experience using:
- Deep learning frameworks like TensorFlow or Theano
- Open-source NLP toolkits like Stanford CoreNLP or OpenNLP
- Developing and improving core NLP components--not just grabbing things off the shelf
- Managing large-scale crowd-sourcing data labelling and acquisition (Amazon Turk, Crowdflower, etc.)