Machine Learning Engineer will provide technical direction, execution and support of machine learning strategies for the SCPMG Medical informatics group. The position entails designing and implementing data pipelining, integration, and optimization of machine learning models to address healthcare's triple aim: to improve the health of populations, to lower the cost of care, and to enhance the care experience.
Use statistical and machine learning techniques to develop and improve clinical decision support tools
Design and develop data pipelines for machine learning applications
Optimize machine learning models to scale in real-time streaming applications
Integrate and deploy machine learning components in a production environment
Work closely with machine learning scientists, physicians, and other stakeholders
Lead small/sub-project efforts and provides visibility into team accomplishments to other departments/groups.
Reviews and provides practical feedback on group products and procedures.
Provides technical feedback on team members' work.
Mentors team members acquiring new skills.
Seeks out open-source software packages or existing software code that can be reused or applied to assigned tasks.
Defines the logic, performs coding, tests, and debugs system components.
Develops and enforces current programming standards and change management.
Independently develop and modify testing components/scripts to support required functions.
Guide and help lower level developers in test-driven development (TDD) design/implementation.
Work with subject matter experts (SME) and senior developers to develop comprehensive testing plan/modules for self-developed software components.
Produces/archives process related artifacts such as design documents, test plans, wikis, and code review forms.
Deploys developed products to project environments.
Minimum six (6) years of programming or technical related experience.
B.S. in computer science, informatics, physics, mathematics, engineering or related fields.
License, Certification, Registration
Familiarity with Python and Java, expert in at least one of the two
Experience with pipelining, workflow, and orchestration tools such as Apache Airflow, MLFlow, Kuberflow
Experience with deep learning frameworks (e.g. Tensorflow)
Experience with SQL
Experience with source control tools for both code and models/data
Familiarity with classification and regression algorithms
Demonstrated experience in Natural Language Processing
Demonstrated experience with machine learning integration and deployment in production environments
Demonstrated experience with Tensorflow Serving
M.S. in computer science, informatics, physics, mathematics, engineering or related fields.
Familiarity with C++/CUDA
Familiarity with healthcare terminology.