MLOps Engineer building production ML infrastructure, pipelines, and monitoring for exacare ai’s post - acute care AI platform. Scaling reliable systems that help healthcare teams make safer placement decisions.
About the role
- Machine Learning Engineer developing scalable machine learning systems and models for hospitality solutions at Push Operations. Collaborating remotely, with opportunities to work from Vancouver office.
Responsibilities
- Design, develop and deploy scalable machine learning pipelines/systems for various problems such as sales/labour forecasting, anomaly detection
- Identify and collect relevant data sources required for our projects
- Integrate with external data and AI APIs
- Own machine learning based features end to end, from model experimentation to the end user
- Communicate results with various stakeholders and be able to describe how projects can impact our clients
- Maintain high standards in our team by performing regular code reviews
Requirements
- Masters Degree in a quantitative subject (e.g., Statistics, Data Science, Mathematics, Computer Science)
- 3+ years of experience working as part of a data science or data engineering team
- 5+ years of experience working in a software developer or adjacent role
- Strong background in data science/statistics including time series, regression/classification problems
- Curious, self motivated individual who enjoys solving complex problems and bringing value to customers
- Experience with SQL and ETL pipelines, and Data Warehouses (e.g, Snowflake, Redshift, or other)
- Expert communication skills while speaking to audiences with a range of backgrounds
- A passion for solving real-world problems with technology that makes a difference in people's lives.
Benefits
- Flexible work arrangements
- Professional development opportunities
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