At Baxter, we are deeply connected by our mission. No matter your role at Baxter, your work makes a positive impact on people around the world. You’ll feel a sense of purpose throughout the organization, as we know our work improves outcomes for millions of patients.
Baxter’s products and therapies are found in almost every hospital worldwide, in clinics and in the home. For over 85 years, we have pioneered significant medical innovations that transform healthcare.
Together, we create a place where we are happy, successful and inspire each other. This is where you can do your best work.
Join us at the intersection of saving and sustaining lives—where your purpose accelerates our mission.
Summary:
As a Senior MLOps Engineer, you will report to the Associate Director of Data Science and work closely with other members of the Data team to deploy predictive models as services, build our machine learning infrastructure, and maintain and improve data, modelling and inference pipelines.
Essential Duties and Responsibilities.
Software architecture and leadership
Hire, mentor and coach a team of 1-2 data engineers in the next 12 months
Set technical direction for the team by proposing technologies, tools, languages that can be used to solve technical and business problems using ML/DL on AWS,
Document and size project planning in JIRA. Provide estimates around project completion and communicate acceptance criteria
Machine Learning Engineering (MLOPS)
Set up backend services in Python that support predictive models or third-party integrations. This will involve the following:
Writing business execution logic for the service
Ensure full development lifecycle for e2e ML solutions (MLFlow, AIHUB)
Writing tests (unit, integration, regression, property, smoke, and e2e tests)
Setting up logging, monitoring and alerting
Setting up a CI/CD pipelines via Jenkins
Troubleshoot, identify, and fix defects through debugging, profiling, logging, or log analysis via CloudWatch / Splunk
Document technical designs in Confluence or GitHub Readmes
Data Infrastructure
Automatic ingestion of data from production and other external services into the Data Lake (S3) and Data Warehouse (Snowflake).
Setting up data infrastructure monitoring and alerting
Manage the data engineering backlog and data product requirements
Support cross-functional requirements gathering from engineering/product management, analytics and data science
Reasonable Accommodations
Baxter is committed to working with and providing reasonable accommodations to individuals with disabilities. If, because of a medical condition or disability, you need a reasonable accommodation for any part of the application or interview process, please send an e-mail to [email protected] and let us know the nature of your request along with your contact information.
Recruitment Fraud Notice
Baxter has discovered incidents of employment scams, where fraudulent parties pose as Baxter employees, recruiters, or other agents, and engage with online job seekers in an attempt to steal personal and/or financial information. To learn how you can protect yourself, review our Recruitment Fraud Notice.
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