Senior Machine Learning Engineer
Brisbane, Australia or Remote
ResApp Health is developing digital healthcare solutions to assist doctors and empower patients to diagnose and manage respiratory disease using only a smartphone. We are a small team that combines cutting-edge Machine Learning technology with world-class clinical science to deliver breakthrough mobile health solutions and solve real healthcare problems. ResApp is listed on the ASX (ASX:RAP) and headquartered in Brisbane, Australia.
In this role you will be part of our algorithm Research and Development team, bringing our cloud based data and machine learning infrastructure up to a world class level. Our algorithms are centred around using audio, so you’ll also work in digital signal processing. We use a multitude of machine learning techniques, from logistic regression models and hand-crafted features through to deep learning neural networks.
- Take a cloud first approach to infrastructure that helps the team efficiently develop, train and test new audio diagnostic ML models at scale
- Develop and own data storage, analysis and ingestion into our algorithm training runs
- Collaborate with the ResApp product team to implement machine learning algorithms on smartphones
- Work closely with our DevOps engineers to ensure pipelines and storage adhere to best practices and are well logged, monitored, regulatory compliant and reliable
- BS or higher in Computer Science, Data Science or Machine Learning, or equivalent years of experience
- Previous experience in machine learning in a cloud environment (AWS, Azure, GCP)
- At least 3 years experience with building out and maintaining data pipelines (ETL/ELT) within AWS using Python/Spark/Scala
- Experience in one or more of C++, Python or R
- Familiar with the development tools used to commit and collaborate on code (Jira, Github)
- Masters or PhD in Machine Learning or Data Science
- 2 or more years commercial machine learning and/or audio signal processing experience
- Experience with machine learning frameworks (PyTorch, Sagemaker, tensorflow etc)
- Experience optimising accelerated (GPU) containers to parallelise model training
- Solid knowledge of classifiers (e.g. logistic regression, neural networks, etc), feature engineering and feature selection
To apply please send a cover email and a copy of your resume to email@example.com.