Position summary

The Intern – Machine Learning Engineer will support building of AI 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 an intern part of Data Science and Artificial Intelligence team you will be working on structured/unstructured data to build machine learning models and support existing engineering applications for information retrieval applications.

Some of these applications include but are not limited to provider matching, advanced risk intelligence system, optical character recognition, understanding the contents of the medical documents using natural language processing, and integrating processes into the overall AI pipeline to mine healthcare and medical information with high recall and other relevant metrics. We ingest claims, medical charts, etc. from providers containing 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.
Essential functions

The Intern Machine learning engineer will have the opportunity to provide value and contribution to the Data science team, shape team culture and operating norms as a result of the fast-paced nature of a new, high-growth organization.

Required Skill Sets

• Bachelors and above from Engineering/Computer Science/Data Science/Statistics/Mathematics
• Academic background in Data Science with good understanding of Statistics and Machine Learning skills
• Strong programming knowledge on algorithms, data structure and additional software engineering skills in an industry setting
• Exposure to Programming Languages – Python, R, Java, Scala, Julia, C++
• Scripting Skills – SQL, Unix
• Exposure or Knowledge on Dockers and Kubernetes
• Knowledge using Flask and or additional frameworks to build REST API’s

Roles and Responsibilities

• Take part in Development and maintenance of machine learning and data science products
• Work with Lead, immediate managers, and stakeholders to understand requirements and deliver efficient models, visualization, research outcomes, and products
• Ability to communicate and collaborate effectively with peers, Leads, managers, and stakeholders on delivery, issues, and expectations
• Writing efficient code, provide production support, use automated testing, use continuous build, and deploy tools
• Inclination towards learning Visualizations for monitoring model performance and KPI’s
• Support documentation of work and products using tools like but not limited to confluence, power point, word, JIRA, Bitbucket, GitHub, etc.
• Written and verbal technical communication skills with a learning aptitude of present complex technical information in a clear and concise manner to a variety of audiences

Nice to Have

• Knowledge of Software engineering skills, CICD, MLOPS
• Knowledge of cloud platforms like Azure / AWS / GCP (or similar cloud)
• Masters/PhD
• Contribution to open source/publication in Journals
• Knowledge or courses on Dockers and Kubernetes