ML Engineer II

Waystar•Louisville, KY

About The Position

We are looking for an outstanding, brilliant, and driven Machine Learning Engineer to join our growing Advanced R & D team. In this mission critical role, the Application Engineer will design, build, and implement amazing web applications and back-end services for our internal customers. They will also have the opportunity to work with cloud-based components and generative AI services on the Google platform.

Requirements

Bachelor's or Master's degree in Computer Science, Machine Learning, Data Science, or a related quantitative field.
2-4 years of professional experience in machine learning engineering or a related role.
Proficiency in Python and relevant machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch).
Experience with data manipulation and analysis tools (e.g., Pandas, SQL).
Solid understanding of machine learning principles, algorithms, and statistical modeling techniques.
Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and MLOps tools/practices.
Experience with version control systems (e.g., Git).
Strong problem-solving skills and the ability to work independently and collaboratively within a team environment.
Excellent communication and interpersonal skills.

Nice To Haves

Prior experience in the healthcare industry or with healthcare data is a plus.

Responsibilities

Design, develop, and implement machine learning models and algorithms to solve complex business problems in the healthcare domain.
Work with large and diverse datasets, performing data cleaning, feature engineering, and data analysis to prepare data for model training.
Build, train, and evaluate machine learning models using various frameworks and tools.
Develop and maintain robust MLOps pipelines for model deployment, monitoring, and retraining.
Collaborate closely with data scientists, software engineers, and product managers to understand requirements and integrate ML solutions into existing products and services.
Conduct experiments and A/B tests to assess model performance and identify areas for improvement.
Participate in code reviews, contribute to architectural discussions, and uphold best practices in software development and machine learning engineering.
Document technical designs, model specifications, and operational procedures.
Stay up-to-date with the latest advancements in machine learning, artificial intelligence, and related technologies.

Benefits

Competitive total rewards (base salary + bonus, if applicable)
Customizable benefits package (3 medical plans with Health Saving Account company match)
We offer generous paid time off for our non-exempt team members, starting with 3 weeks + 13 paid holidays, including 2 personal floating holidays.
We also offer flexible time off for our exempt team members + 13 paid holidays
Paid parental leave (including maternity + paternity leave)
Education assistance opportunities and free LinkedIn Learning access
Free mental health and family planning programs, including adoption assistance and fertility support
401(K) program with company match
Pet insurance
Employee resource groups