Please note that New York area opportunities are hybrid only and require 3 days in office weekly at our financial district location in Manhattan.
- Developing NLP systems that help us structure and understand biomedical information and patient records
- Using a variety of structured and unstructured data sources
- Imagining and implementing creative data-acquisition and labeling systems, using tools and techniques like crowdsourcing and novel active learning approaches
- Working with the latest NLP approaches (BERT, Transformer)
- Training your models at scale (Horovod, Nvidia v100s)
- Employing and iterating on scalable and novel Machine Learning pipelines (Airflow on Kubernetes)
- Reading and integrating state of the art techniques into Fathom's ML infrastructure such as Mixed Precision on Transformer networks
- 2+ years of Software Engineering experience in a company/production setting
- Knowledge of algorithms, data structures and systems design, with a focus on building sound and scalable ML
- Experience with deep learning frameworks like TensorFlow or PyTorch
- Industry or academic experience working on a range of ML problems, particularly NLP
- A real passion for finding, analyzing, and incorporating the latest research, technologies and techniques directly into a production environment
- Good intuition for understanding what good research looks like, and where we should focus effort to maximize outcomes
- A desire to collaborate in office 3 days weekly
- Developed and improved core NLP components and not by just 'grabbing things off the shelf'
- Led large-scale crowd-sourcing data labeling and acquisition (Amazon Turk, Crowdflower, etc.)
Salary range:
- $100 000 - $175 000 USD