769 million! That's how many lives our products touched in 2020.. The Associate Director, DevOps, MLOPS Engineer will be responsible for the support and development of state-of-the-art DevOps Infrastructures, data pipelines that and scalable machine learning deployment for information and analytics product development. These products support initiatives of US Health Economics & Outcomes Research, Medical Access, and Population Health and Account Management on various goals. Information and analytic products span the spectrum from rigorous protocol driven studies to exploratory analyses that incorporate modern statistical methods and the development of industrial data pipelines and analytic deployment to create disruptive efficiency. These products use a broad range of technologies and are developed in an agile fashion able to handle the complexity of driving value and innovation inside the organization and health system.

Your key responsibilities:
Develop, deploy and manage software DevOps infrastructures together with software production pipelines and RWE and Data Science data pipelines that continuously build and deploy information products and transform raw data from disparate data sources to feed Machine Learning and statistical analyses. These information products will be used for dynamic visualizations, reports, and peer-reviewed journal publications and will drive advanced analytics to create the Real World Evidence and Medical Intelligence to reimagine and innovate patient access and optimize healthcare efficiency.

* Design the software production and data pipelines and engineering infrastructure to support our software production lifecycle and machine learning systems at scale
* Develop and deploy scalable tools and services for information products to handle machine learning training and inference
* Identify and evaluate new technologies to improve performance, maintainability, and reliability of our software lifecycle and machine learning systems
* Apply software engineering rigor and best practices to machine learning, including CI/CD, automation, etc.
* Support software and model development, with an emphasis on auditability, versioning, and data security
* Work with the Machine Learning / Statistical leaders to execute innovative analytic product development across methodology domains spanning health economics, epidemiology, implementation science, and quality improvement projects.
* Drive disruptive efficiency through a culture of continuous improvement by providing leadership to the data engineering contractors to apply development operations best practices.

What you'll bring to the role:
Essential:
* Position can be remote.
* B.S. in computer science or related field, Masters degree preferred
* 5+ years of professional software engineering development creating backend databases and creation of scalable data engineering workflows to support machine learning model development
* Experience building end-to-end systems as a Platform Engineer, ML, DevOps Engineer, or Data Engineer (or equivalent)
* Strong software engineering skills in complex, multi-language systems with extensive experience in utilizing object-oriented programming
* Experience working with cloud computing and database systems, building custom integrations between cloud-based systems by writing and consuming APIs, and developing containers and Kubernetes.
* Experience developing and maintaining software productions and ML systems built with open-source tools
* Familiarity with one or more data-oriented workflow orchestration frameworks (KubeFlow, Airflow, Argo, etc.)
* Strong understanding of software testing, benchmarking, and continuous integration also using methodologies like TDD and BDD
* Expert in Python, SQL, shell

Desirable requirements:
* Well-rounded experience with many programming languages (e.g., JavaScript, html, C++, etc...).
* Experience with many database systems such as SQL, NoSQL, graph databases.
* Experience in machine learning modeling parallel computing and/or statistical analyses.
* Experience in healthcare data (Electronic Health Records, Insurance Claims).
* Experience with R.