Senior AI Engineer

Sift Healthcare is seeking an AI Engineer to join our highly collaborative, growing analytics group. This hire will work closely with our data science, ML/DevOPs, and engineering teams to enhance Sift’s machine learning and AI infrastructure, techniques, and practices.

Sift is transforming healthcare payments by equipping healthcare organizations to fully leverage their payments data to work smarter, protect their margins and accelerate cash flow. Large health systems, leading HCIT vendors, payers and outsourced revenue management agencies use Sift's Payments Intelligence Platform, ML integrations and advanced analytics to optimize payment outcomes and enable data-driven decision-making within the revenue cycle.

The AI Engineer is a key member of the Data Science team, responsible for improving and enhancing Sift’s suite of predictive models and operations that work to solve complex healthcare payment problems. We are seeking a candidate with 5+ years of experience in an AI or deep learning role, with an advanced degree (MS or higher) in a related field.

A key attribute of the employee will be their ability to test hypotheses and present findings to upper management, both internally and externally, and help other team members do the same. They must be collaborative and have strong communication skills. The employee must develop a deep understanding of the data Sift utilizes, provide advanced analysis, and suggest how Sift Healthcare can improve current AI and deep learning techniques and infrastructure.

The employee is expected to remain up to date with current ML and GenAI trends.

Experience working with PII/PHI/HIPAA data is required. Experience working with healthcare data is required. A Wisconsin resident is preferred for this role.

• Generative AI & LLMs, Monitoring and Observability:
  Utilization and deployment of LLMs for clinical decision support, and revenue-cycle automation. Implement systematic LLM evaluation and monitoring, including task-level metrics, LLM-as-a-judge scoring, and detection of input, embedding, and output drift to ensure stable production performance.
• Retrieval:
  Build and optimize RAG pipelines, including document ingestion, chunking, embeddings, and retrieval. Implement evaluation and monitoring frameworks to assess retrieval and generation quality and detect drift in data, embeddings, and outputs.
• Deep Learning:
  Research, develop, and optimize deep learning models for healthcare revenue-cycle applications, from experimentation and training through evaluation and assisting with deployment. Leverage embedding architectures such as Titan
  
  V2 and Clinical
  
  BERT variants, along with other transformer-based models, to understand clinical documentation, denials, and payer communications.
• Unsupervised & deep clustering:
  Design deep clustering pipelines, leveraging techniques such as HDBSCAN for scalable density-based clustering and IDEC (Improved Deep Embedded Clustering) for joint representation learning and clustering.
• Best practices & compliance:
  Uphold rigorous code quality standards, conduct peer reviews, adhere to Git workflows, and ensure HIPAA-compliant handling of PII/PHI data.
• Cross-functional collaboration:
  
  Partner with Data Scientists, ML & Dev Ops, Engineers, and Product teams to integrate deep learning capabilities into our platform and drive data-driven features.

• Educational background:
  Bachelor’s or Master’s in Computer Science, Engineering, or related field; advanced degree strongly preferred.
• Hands-on Deep Learning and GenAI experience: 5+ years building and deploying GenAI or deep learning models (Tensor Flow, PyTorch) in production settings.
• LLM & NLP expertise:
  Practical experience with transformer architectures, prompt engineering, and retrieval-augmented generation workflows.
• ML Ops proficiency:
  Familiarity with containerization (Docker), orchestration (Kubernetes), and CI/CD pipelines.
• Healthcare data knowledge:
  Working understanding of claims, clinical documentation, and HIPAA requirements for PII/PHI data.
• Coding skills:
  Strong Python proficiency, debugging skills, Git-based version control, and collaborative code review.
• Communication & teamwork:
  Excellent written and verbal communication, with the ability to translate complex models into business impact.
• Management experience a plus.

Compensation will be based on skills, experience, and performance.

Sift is a data science company working to improve payments operations and outcomes in the healthcare industry. We are a growing and dynamic team that is serious about technology. Based in Milwaukee, Wisconsin, Sift is thriving and looking for motivated team members who will help shape our culture. Sift offers competitive salaries and benefits. Learn more about Sift at