Machine Learning Engineer

Salud Revenue Partners (Salud) is a technology-enabled service company with leadership and a high-performance culture that partners with healthcare providers nationwide to improve their revenue cycle performance.

Our vision is to be a national model for the delivery of revenue cycle services. We are at the forefront of innovation, applying next generation process automation and artificial intelligence to focus on the most productive work to help healthcare organizations resolve difficult accounts receivable, find gold in zero balance accounts, achieve the highest coding accuracy, and carry out patient-centered solutions to self-pay.

At Salud Revenue Partners, you can work for an organization dedicated to your employee development as well as delivering unparalleled results for our customers. We give staff objectives, exceptional training, and technology-enabled resources to accomplish goals and then set them free to get the job done. We encourage fresh ideas and a collaborative approach to delivering industry-leading solutions to clients.

What do our staff say about Salud? In May 2025 we were certified a Great Place to Work (for the 3rd year in a row), below are a few of our survey results:

• 97% of our employees say this is a great place to work!
• 97% of our staff say, "When you join the company, you are made to feel welcome."
• 97% of our employees say, "When I look at what we accomplish, I feel a sense of pride."
• 99% of our employees say, "People are encouraged to balance their work life and their personal life."

Role Overview
We are hiring a Senior Machine Learning Engineer / Data Scientist to help bring AI solutions to life across predictive modeling, NLP, and recommendation systems. You'll work alongside the Lead Data Scientist to deliver machine learning models that span structured prediction, language understanding, and personalization. This is a hands-on role ideal for someone excited to work on real-world data, build production-ready models, and shape best practices from the ground up.

Key Responsibilities:

• Deliver Predictive Modeling Solutions
  Build and tune machine learning models using structured data for use cases such as forecasting, classification, and risk scoring. These models will support decision-making, automation, and operational efficiency.
  
• Design NLP Models
  Develop NLP models for document classification, entity recognition, and semantic understanding using both traditional methods and modern deep learning architectures like transformers. Apply these solutions to optimize communication workflows and unstructured data analysis.
  
• Implement Recommendation Engines
  Build recommendation systems that support personalization and content ranking using collaborative filtering, content-based methods, and hybrid techniques. Help guide product or user decisions based on behavioral or contextual data.
  
• Collaborate on Data and Infrastructure
  Partner with data engineering to access, prepare, and pipeline structured and unstructured datasets. Contribute clean, testable code and participate in MLOps workflows including version control, containerization, and monitoring.
  
• Deploy and Monitor Models in Production
  Integrate machine learning models into software products or workflows. Monitor their performance and accuracy over time, manage retraining needs, and troubleshoot production issues as necessary.
  
• Document and Communicate Work
  Maintain clear documentation for models, datasets, and experiments. Share results with stakeholders and ensure reproducibility, transparency, and alignment with business goals.
  

Qualifications:

• Education: Master's or PhD in Data Science, Computer Science, Engineering, or a related field.
• Experience: 3-6 years of experience developing models in at least two of the following areas: structured prediction, NLP, or recommendation systems.
• Technical Skills: Proficient in Python, with experience using libraries such as scikit-learn, PyTorch, TensorFlow, and Hugging Face. Experience deploying models in production environments and working with tools like Docker, MLflow, or Airflow.
• People Skills: Strong communication skills and ability to collaborate across technical and non-technical teams.
• Location & Work Arrangement: We prefer candidates who can collaborate on-site with our team in West Lafayette, IN periodically. We support a hybrid work model, you'll have flexibility to work from home part of the week while joining the team in person for key meetings, brainstorming sessions, and project kick-offs.

This job operates in a professional cubicle or home office environment where standard office equipment such as computer, phones, photocopiers, filing cabinets and fax machines are utilized. The noise level in the work environment is usually minimal.

This is a full time, exempt position with the expectation that the employee will work 40+ hours a week.

• Supervisory Responsibility: This position has no supervisor responsibilities.
• Physical Demands: While performing the duties of this job, the individual is regularly required to stand, bend, kneel, sit, walk, and use hands to touch, type, handle, or feel objects; reach with hands and arms; talk and hear. The vision requirements include close vision, distance vision, color vision, peripheral vision, depth perception and the ability to adjust focus. Individual may occasionally lift and/or move up to 10 pounds.
• Travel: Travel when necessary for client work or training may be needed periodically for this position.