Staff Machine Learning Engineer at Revecore

, , United States -

Full Time

Start Date

Immediate

Expiry Date

05 Jan, 26

Salary

0.0

Posted On

07 Oct, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Data Analysis, Software Engineering, Python, Scikit-Learn, TensorFlow, PyTorch, Data Wrangling, Exploratory Data Analysis, Natural Language Processing, Spark, Cloud MLOps, Model Deployment, Statistical Analysis, Causal Inference

Industry

Hospitals and Health Care

Description

Our Company: Start your next chapter at Revecore! For over 25 years, we’ve been at the forefront of specialized claims management, helping healthcare providers recover meaningful revenue to enhance quality patient care in their communities. We’re powered by people, driven by technology, and dedicated to our clients and employees. If you’re looking for a collaborative and diverse culture with a great work/life balance, look no further.  As part of our team, you’ll be rewarded with: * Comprehensive medical, dental, vision, and life insurance benefits from the start of your employment * 12 paid holidays and flexible paid time off * 401(k) contributions * Employee Resource Groups that build community * Career growth opportunities * An excellent work/life balance Location: Remote – USA As a Machine Learning Engineer at Revecore, you will: Use your expertise in machine learning, exploratory data analysis, and software engineering to enhance the productivity and efficiency of our underpayment business. You will work on projects with purpose, such as prioritizing claims based on expected recovery dollars and improving our claim-remit matching process. This is a modeling team that owns the model deployment process. You won’t be building dashboards or pivot tables. You won't just build POCs. Our team increases revenue and decreases costs: you will deploy your work and see the results as we increase our client hospitals' revenue. The Role: * 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 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 become the team’s expert in your specialization, and you will learn from experts in theirs. You’ll be successful if you have: * An urge to question assumptions, and to get it right (or at least good enough) even if your first idea is wrong. * A commitment to collaborate, rather than go off in a corner only to appear when you need to submit a pull request. * A bachelor's degree in any data-centric field. Scientific thinking is a must. 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. TensorFlow or PyTorch is a plus. * Ability to wrangle data, perform exploratory data analysis, and draw insights from visualizations. It would also be great if you have: * Intuition about data developed by doing statistics and/or research. Bonus points if you know the difference between MAR and MCAR, or can draw causal inferences from historical data. * 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. Work at Home Requirements: * A quiet, distraction-free environment to work from in your home.   * A secure home internet connection with speeds >20 Mbps for downloads and >10 Mbps for uploads is required. * The workspace area accommodates all workstation equipment and related materials and provides adequate surface area to be productive.   Revecore is an equal opportunity employer that does not discriminate based on race, color, religion, sex or gender, gender identity or expression, sexual orientation, national origin, age, disability status, veteran status, genetic information, or any other legally protected status.       We believe that a diverse workforce fosters innovation and creativity, enriches our culture, and enables us to better serve the needs of our clients and communities. We welcome and encourage individuals of all backgrounds, perspectives, and abilities to apply.  Revecore is an equal opportunity employer that does not discriminate based on race, color, religion, sex or gender, gender identity or expression, sexual orientation, national origin, age, disability status, veteran status, genetic information, or any other legally protected status.     We believe that a diverse workforce fosters innovation and creativity, enriches our culture, and enables us to better serve the needs of our clients and communities. We welcome and encourage individuals of all backgrounds, perspectives, and abilities to apply. Must reside in the United States within one of the states listed below: Alabama, Arkansas, Delaware, Florida, Georgia, Iowa, Illinois, Indiana, Kansas, Kentucky, Louisiana, Massachusetts, Maine, Maryland, Michigan, Minnesota, Missouri, Mississippi, Montana, North Carolina, Nebraska, New Hampshire, Ohio, Oklahoma, Pennsylvania, Rhode Island, South Carolina, Tennessee, Texas, Virginia, Wisconsin, or West Virginia.

Responsibilities

Own end-to-end development, training, deployment, evaluation, and improvement of machine learning systems to rank claim opportunities. Collaborate with cross-functional teams to design and build practical solutions that drive business impact.