Senior AI/ML Engineer

Health Catalyst

Health Catalyst is expanding and maintains a large suite of Improvement Apps that contribute to healthcare analytics and process improvement solutions. This includes products that manage the care of health system populations, better serve patients at the point of care, reduce health system costs, and reduce clinician workload.

Job Summary:

As a Senior AI/ML engineer, you will be working with diverse Improvement Apps, software engineering team designing, developing, and maintaining various platforms that serve internal HCAT team members, clinicians, and patients. You will rely on Test-Driven Development to safely enhance and refactor our system, shipping production code multiple times per week. And you will go to bed each night with the comfort that your code is improving outcomes for patients.

If you love…

Help drive clarity and prototype individual features or problems

Knowledge of architecture patterns and the ability to design and complete features / tasks that are 50-60% well defined.

Can discern where gaps can be filled in without consulting a Product Manager or another programmer and can judge when a consultation is needed.

Work is reviewed with the occasional need for material direction or implementation changes

Seeks and provides guidance via PR reviews, pair-programming and other interactions with Engineers and Product Managers

It is second nature to develop high code quality standards balanced with the needs of real-world customer timelines.

Possesses a passion and drive to deliver exceptional products and follows established patterns and approaches within existing code bases with ease.

Takes ownership of learning and growth

Capitalizes on internal and external opportunities for learning.

Identifies gaps in knowledge/skills and seeks ways to close those gaps (self-guided learning, pairing, seeking guidance for yourself and developing guidance for less experienced members of the team)

Periodic On Call Rotation

Ability to communicate with Customer Success about customer issues that are escalated to Engineering and help quantify customer impact.

Can Respond quickly to operational emergencies, find short term resolutions and plan long term fixes to avoid similar issues in the future.

What you own in the role:

• Design, develop, and deploy

  machine learning models and AI solutions

  for real-world business problems.
• Implement

  MLOps pipelines

  to automate model training, testing, deployment, monitoring, and retraining.
• Collaborate with data engineering teams to ensure

  clean, reliable, and scalable data pipelines

  .
• Optimize model performance and scalability across large datasets and distributed environments.
• Integrate ML models into production systems with APIs and microservices.
• Work with cloud platforms (

  AWS, Azure, or GCP

  ) to manage compute, storage, and ML services.
• Proficiency in SQL for data manipulation and analysis
• Establish monitoring, logging, and alerting solutions for ML model performance and data drift.
• Contribute to architecture design, technical roadmaps, and best practices in ML engineering.
• Mentor junior team members and contribute to knowledge sharing across the organization.
• Experience with

  large language models (LLMs)

  , generative AI, or reinforcement learning.
• Knowledge of

  data versioning tools

  (DVC, Delta Lake, LakeFS).
• Familiarity with

  feature stores

  and advanced monitoring for ML pipelines.

What you bring to this role:

• Bachelor’s/Master’s degree in Computer Science, Data Science, AI/ML, or related field (PhD a plus).
• 6+ years of experience in

  AI/ML engineering

  with a proven track record of building and deploying models.
• Strong knowledge of

  Python

  and ML frameworks (

  TensorFlow, PyTorch, Scikit-learn

  ).
• Hands-on experience with

  MLOps tools

  (MLflow, Kubeflow, SageMaker, Vertex AI, Airflow, etc.).
• Solid understanding of

  DevOps principles

  (CI/CD, Docker, Kubernetes, GitOps) in ML workflows.
• Experience with

  data preprocessing, feature engineering, and model evaluation techniques

  .
• Knowledge of

  cloud environments

  (AWS/GCP/Azure) and cloud-native ML services.
• Strong understanding of

  data science fundamentals

  (supervised/unsupervised learning, deep learning, NLP, etc.).
• Excellent communication and collaboration skills.
• An understanding of healthcare data is a plus, but not a requirement

You may also bring:

Experience with cloud infrastructure and architecture patterns, either Azure or AWS preferred.

Software development experience within healthcare IT and understands key data models (clinical, claims, financial, etc.) and interoperability standards such as HL7v2, CDA, EMR, and FHIR

Knowledge of healthcare compliance and how it applies to Application Security

Agile/Scrum software development practices

Business Intelligence or Data warehousing experience

Preferred Experience and Education:

BS/BA or MS in Computer science, information systems, or other technology/science degree.

A minimum of 6 years of experience in building commercial software, SaaS, or digital platforms.

Equal Employment Opportunity has been, and will continue to be, a fundamental principle at Health Catalyst, where employment is based upon personal capabilities and qualification without discrimination or harassment on the basis of race, color, national origin, religion, sex, sexual orientation, gender identity, age, disability, citizenship status, marital status, creed, genetic predisposition or carrier status, sexual orientation or any other characteristic protected by law.. Health Catalyst is committed to a work environment where all individuals are treated with respect and dignity.