What You’ll Be Doing:

The Senior Cloud Machine Learning Engineer will support building of Data Science and Machine Learning products in Agile fashion that empower healthcare payers, providers, and members to quickly process medical data to making informed decisions and overall reduce health care costs. As a Sr Cloud Machine learning engineer part of Data Science and Artificial Intelligence team you will be working primarily on build machine learning models and Deploying Models on various cloud platforms including but not limited Azure and AWS platforms.  These applications include but are not limited to Computer vision & optical character recognition, Patient Risk Models, Fraud, Waste and Abuse, understanding the contents of the medical documents using natural language processing, predictive modeling using unsupervised and supervised approach on structured data, and integrating the processes into the overall AI pipeline. We ingest claims, medical charts, etc. from providers containing Structured and unstructured data which will be transformed into structured data to support automated entry into our storage layers for downstream applications. The results will be used dually for real-time operational processes with both automated and human-based decision making as well as contribute to reducing healthcare administrative costs. We work with all major cloud and big data vendors offerings including but not limited to (Azure, AWS, Google, IBM, etc.) to achieve AI goals in healthcare and support Evolent business.

Roles and Responsibilities:

• Transition and/or maintain AI existing applications on cloud and build new AI & ML applications which are cloud native
•  Develop, maintain, and improve algorithms, data pipelines, automated processes, and services to create a data science backed solution that meets a business needs and support Evolent Health business objectives, products and improve processing efficiency, reducing overall healthcare costs
• Takes full stack ownership by consistently writing production-ready and testable code.
• Consistently creates optimal design adhering to architectural best practices; considers scalability, reliability and performance of systems/contexts affected when defining technical designs.
• Transition and/or maintain AI existing applications on cloud and build new AI & ML applications which are cloud native
• Support MLOps or Machine learning DevOps for existing applications
• Gather external data sets; build synthetic data and label data sets as per the needs for Data Science and Machine Learning
• Apply software engineering skills to build Data Science & ML products to improve automation and improv business and user experience
• Work closely and collaborate with Data Scientists, Machine Learning engineers, IT teams, Dev Ops team and Business stakeholders to achieve business goals
• Build Data Science and ML products — from platforms to systems for model training, versioning, deploying, storage, and testing models with creating real time feedback loops to fully automated services
• Provide support to additional Data Science team members

The Experience You’ll Need (Required):

• BS degree or above in Computer Science or related STEM fields
• 5+ years of Industry experience related to Data Science, Machine Learning, Model deployment and maintaining models in production.
• Good experience with data science approaches like sampling techniques, feature engineering, classification, and regressions, SVM, trees, Deep learning, model evaluations etc.
• Good understanding of mathematical concepts including but not limited to linear algebra, Advanced calculus, partial differential equations, and statistics
• Strong Software Engineering experience including understanding of concepts in data structures, algorithms, unit testing, CICD, Dev OPS, Agile delivery, etc.
• Good understanding and experience of distributed and high-performance computing platforms  
• 3+ years of building rest API using microservice architecture and Scheduling Batch job using Flask, AWS Lambda, Azure Functions, Airflow etc.
• Experience with AWS and Azure services, Serverless Architectures, ML DevOps and CICD  
• Experience with developing and deploying products in production with experience in two or more of the following languages (Required: Python | additional one in either: C++, Java, Scala)
• Good Unix/Linux background especially with Ubuntu/Rhel and working with IT Teams to have the platform available for 24x7x365 days a year
•  3+ years of experience with at least one of the following cloud vendors like AWS, Azure, and their services

Finishing Touches (Preferred):

• 2+ years of Team lead experience and mentoring team members around software code development and ML model development
• Experience with Kubernetes and dockers   
• Experience working with team members spread globally