AWS DevOps Engineer

Position: AWS/DevOps Engineer

Location: San Francisco, CA

Contract: Long term

Job Description:

In this role you will work closely with our data science, machine learning, and data infrastructure team area of Commercial, Medical, and Government affairs.These organizations partner across the U.S.’s healthcare systems to deliver ever-better health outcomes for patients while lowering overall healthcare costs. Your work will impact the way our customers experience AI/ML. Put another way, this role is absolutely critical to the long term scalability of our core Products in Data Science. This product "Data Science & Machine Learning" builds and executes on the strategy for Data Science and Machine Learning to further advance our products for patients. This also covers responsibility for platforms such as recommendation engines and the delivery of relevant, timely, and action-oriented insights to field personnel and other channels

What will you do?

• Design, build and optimize scalable data science/ machine learning infrastructure to support our model development life cycle
• Build abstractions to automate various steps in different ML workflows
• Collaborate with cross functional teams of engineers, data analytics, machine learning experts, and product to build new features
• Leverage your experience to drive best practices in ML and data engineering
• As part of the early data science team, you will be able to define and implement our initial AWS architecture and our MLOps framework and tools

What do you bring to the table?

• Work experience in AWS based ML OPS and Devops environments
• 5+ years Data Engineering or AWS admin experience in ML ops 
• Proficiency in AWS compatible ML Technologies – AWS - Sagemaker Studio, Tensorflow, Amazon ML Feature Store, model registry, ECR etc 
• Strong understanding of the Kubernetes Platform and container lifecycle management
• Experience with deployment framework such as AWS Cloudformation, CDK, Terraform and Serverless Framework
• Strong organizational skills with ability to work on multiple projects
• Experience with Spark, AWS EMR
• Experience with Continuous Integration & Continuous Delivery using CodePipeline, CodeCommit, CodeBuild or similar technologies 
• Experience with Machine Learning and Data Science platforms like Databricks / Dataiku and experience with advanced data filtering systems