Machine Learning Engineer

Summary

Avita Care Solutions is a healthcare and pharmacy services organization focused on improving health outcomes and access to care. The Machine Learning Engineer will design, deploy, and maintain scalable, compliant machine learning systems using healthcare and pharmacy data to improve patient outcomes, optimize pharmacy operations, and support real-time decision-making.

Responsibilities

• Design, build, deploy, and maintain production-grade machine learning models and pipelines using healthcare and pharmacy data (claims, EHRs, prescription data, formulary data, etc.)
• Develop robust end-to-end ML systems, including data ingestion, feature engineering, model training, validation, deployment, monitoring, and retraining
• Productionize predictive models related to medication adherence, utilization forecasting, cost optimization, and patient outcomes
• Collaborate closely with data scientists, pharmacy experts, clinicians, and engineering teams to translate business and clinical requirements into scalable ML solutions
• Implement MLOps best practices, including CI/CD for ML, model versioning, experiment tracking, performance monitoring, and automated retraining
• Optimize model performance, reliability, and latency for batch and/or real-time inference use cases
• Ensure all ML systems comply with healthcare regulations (e.g., HIPAA) and internal data governance, security, and audit requirements
• Contribute to ML architecture decisions, tooling selection, and platform improvements within the Azure ecosystem
• Document ML systems and communicate technical designs and tradeoffs clearly to both technical and non-technical stakeholders

Skills

• The Machine Learning Engineer will have deep expertise in healthcare and pharmacy data
• • Bachelor's or Master's degree in Computer Science, Machine Learning, Data Science, Engineering, or a related field; or equivalent practical experience
• • 3 years + of experience building and deploying machine learning systems in healthcare or pharmacy domains
• • Strong proficiency in Python for machine learning and software development
• • Solid experience with SQL and working with large-scale relational and cloud-based data stores
• • Hands-on experience implementing and operationalizing machine learning models in production environments
• • Experience with Azure cloud services for ML workloads
• • Familiarity with Databricks and distributed data processing frameworks
• • Experience with ML lifecycle tools for experimentation, deployment, and monitoring
• • Subject matter expert mindset with ability to work independently and work collaboratively to achieve high‑quality outcomes
• • Demonstrates compassion in supporting patients, partners, and team members
• • Strong interpersonal communication skills to collaborate effectively across cross functional teams
• • Applies resourcefulness to solve challenges effectively

Qualifications

Must Haves

• The Machine Learning Engineer will have deep expertise in healthcare and pharmacy data
• • Bachelor's or Master's degree in Computer Science, Machine Learning, Data Science, Engineering, or a related field; or equivalent practical experience
• • 3 years + of experience building and deploying machine learning systems in healthcare or pharmacy domains
• • Strong proficiency in Python for machine learning and software development
• • Solid experience with SQL and working with large-scale relational and cloud-based data stores
• • Hands-on experience implementing and operationalizing machine learning models in production environments
• • Experience with Azure cloud services for ML workloads
• • Familiarity with Databricks and distributed data processing frameworks
• • Experience with ML lifecycle tools for experimentation, deployment, and monitoring
• • Subject matter expert mindset with ability to work independently and work collaboratively to achieve high‑quality outcomes
• • Demonstrates compassion in supporting patients, partners, and team members
• • Strong interpersonal communication skills to collaborate effectively across cross functional teams
• • Applies resourcefulness to solve challenges effectively

Benefits

• This is a remote role, with interviews conducted onsite.
• Healthcare benefits (medical, dental, vision) for eligible team members and their families, along with additional company paid and voluntary benefit offerings.
• Six company paid holidays and three personal floating holidays, paid time off (PTO), paid leaves - two weeks paid parental leave, bereavement, sick leave, time to vote and jury duty, award recognition program, professional learning and development opportunities.
• Company paid benefits – basic life and AD&D, Maven and Health Care Advocate Work/Life Balance Program, health/dependent flexible spending.
• Voluntary benefits – long and short-term disability, pet insurance, legal, accident, hospital indemnity, critical illness, whole and supplementary life insurance, identity theft protection, 401(K) retirement savings plan with company match.