Note: The job is a remote job and is open to candidates in USA. Avita Care Solutions is a healthcare company focused on improving patient outcomes through technology. The Machine Learning Engineer will design and implement machine learning models and systems to enhance pharmacy operations and support data-driven 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
- 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
- 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.
Company Overview