Staff Software Developer responsible for integration architecture in a leading Canadian InsurTech company. Collaborating on Salesforce and other system integrations for streamlined operations.
About the role
- ML Platform Engineer responsible for elevating Afresh's ML infrastructure and enabling faster innovation. Contributing to performance improvements and scalability enhancements for machine learning applications.
Responsibilities
- As an ML Platform Engineer on the ML Platform Engineering team, you will be instrumental in elevating our core ML platform to its next level of performance, reliability, and scalability.
- You'll work on the critical infrastructure that directly enables all of Afresh's Machine Learning and Applied Science teams to innovate faster and deliver impact.
- Your contributions will empower our product suite, including our flagship Prediction Engine, to power replenishment decisions on more than 15% of all produce sold in the United States.
- In your first 3 months, you might deliver a project that helps generalize model configuration, enables no-code model deploys for our various ML solutions, or vastly improves integration testing across our ML systems.
- By the end of your first 6 months, you will have owned the design and implementation of significant scalability improvements and additions to our ML platform.
Requirements
- BS in Computer Science or a relevant technical field.
- 7+ years of professional software development experience with a proven track record of shipping high-quality applications and services.
- Experience working collaboratively with machine learning engineers, data scientists, or applied scientists on large-scale software projects involving machine learning models.
- Technical leadership experience and a demonstrated ability to mentor junior engineers.
- Deep expertise in library design, API design, data structures, and algorithms.
- Strong familiarity with Python.
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