Principal Machine Learning Engineer

Revecore is a leading company in specialized claims management, dedicated to enhancing healthcare providers' revenue recovery. As a Principal Machine Learning Engineer, you will leverage your machine learning expertise to improve the efficiency of the underpayment business and work on impactful projects to increase revenue for client hospitals.

Responsibilities:

• Own end-to-end development, training, deployment, evaluation, and improvement of machine learning systems to rank claim opportunities
• Analyze and explore data to identify actionable opportunities from internal and 3rd party data
• Research, implement, and launch new model architectures that drive business impact
• Partner and collaborate with cross-functional teams of software engineers, data engineers, subject matter experts, product managers, and analysts to design and build practical solutions
• Implement cloud MLOps and AIOps best practices to streamline the development, deployment, and maintenance of machine learning models
• Continuously measure the impact of the AI-enabled workflows on key business metrics and use these measurements to improve the machine learning models and workflows
• Learn from and teach your teammates. You will be the team's expert in your specialization, and you will learn from experts in theirs
• Own a workstream. You'll be the technical lead for the workstream, partnering with others to deliver. This includes guiding the work of and mentoring a less-senior teammate. You'll also work on other projects, but this workstream will be one of your key successes
• Have a voice in Revecore's strategy in your areas of expertise while still being primarily a hands-on-keyboard individual contributor

Requirements:

• A bachelor's degree in any data-centric field
• Experience working in a similar role, with a focus on machine learning or data science
• Experience developing and deploying machine learning models in a production environment
• Strong experience with Python, including scikit-learn
• Ability to wrangle data, perform exploratory data analysis, and draw insights from visualizations
• Intuition about data developed by doing statistics and/or research
• Applied experience with contemporary natural language processing (NLP) techniques and tools (e.g., entity extraction, transformers, Hugging Face)
• Experience with Spark
• Experience with operating ML pipelines in a cloud platform (e.g., AWS, GCP, Azure)
• A master's degree, Ph.D., or other experience demonstrating scientific thinking