MLOPs Engineer

Job Description:

Experience Range: 5 to 12 yrs (min 4 years relevant)

Responsibilities:

Enable Model tracking, model experimentation, Model automation

Develop ML pipelines to support 

Develop MLOps components in Machine learning development life cycle using

Model Repository (either of): MLFlow, Kubeflow Model Registry

Machine Learning Services (either of): Kubeflow, DataRobot, HopsWorks, Dataiku or any relevant ML E2E PaaS/SaaS.

Work across all phases of Model development life cycle to build MLOPS components.

Build the knowledge base required to deliver increasingly complex MLOPS projects on the Cloud Azure

Be an integral part of client business development and delivery engagements across multiple domains

Qualifications & Experience:

Strong experience in System Integration, Application Development or Data-Warehouse projects across technologies used in the enterprise space

Basic Knowledge of MLOps, machine learning and docker

Object-oriented languages (e.g. Python, PySpark, Java, C#, C++ )

Database programming using any flavors of SQL

Knowledge of Git for Source code management.

Ability to collaborate effectively with highly technical resources in a fast-paced environment.

Ability to solve complex challenges/problems and rapidly deliver innovative solutions.

Foundational Knowledge of Cloud Computing Azure.

Hunger and passion for learning new skills

Primary Responsibilities:        

Develop and implement AI and machine learning strategies to drive healthcare solutions, build and test machine learning and deep learning models

Build robust machine learning pipelines to support production processes

Process and transform source data to be used in machine learning pipelines, leveraging cloud computing

Collaborate with cross-functional teams to determine applicability of AI to business problems 

Communicate findings with business stakeholders and collaborate to develop solutions that meet customer needs

Develop code and model documentation and assist with model governance approvals

Clearly document and following best coding practices with Python packages, etc. along with the use of GitHub

Create and present presentations in the form of presentations and written documents of analysis results to Optum AI and business leaders