Be a pioneer in business, education, and global impact by joining this team - a “startup with assets,” where you will have the chance to deploy cutting-edge digital- and emerging-technology education solutions. Where else can you make a difference at the intersection of cutting-edge technology, world-class education, noble purpose, and timeless legacy?

As a Machine Learning Engineer, you will collaborate with data scientists, product managers, and data engineers to operationalize machine learning models in production and manage the lifecycle of artificial intelligence algorithms on a variety of domains. You will develop and deploy novel approaches to optimize existing machine learning systems to maximize their business value.

Duties and Responsibilities:

• Architect, build, maintain, and improve new and existing suite of algorithms and their underlying systems.
• Automate machine learning pipelines and monitor and optimize machine learning solutions.
• Implement end-to-end solutions for batch and real-time algorithms along with requisite tooling around monitoring, logging, automated testing, performance tuning, and A/B testing.
• Use your entrepreneurial spirit to identify new opportunities to optimize business processes, improve consumer experiences, and prototype solutions to demonstrate value.
• Work closely with data scientists and analysts to create and deploy new product features online and in mobile apps.
• Establish scalable, efficient, automated processes for data analyses, model development, validation and implementation.
• Write efficient and well-organized software to ship products in an iterative, continual-release environment.
• Contribute to and promote good software engineering practices across the team.
• Mentor and educate team members to adopt best practices in writing and maintaining production machine learning code.
• Actively contribute to and re-use community best practices.
• Monitor, debug, track, and resolve production issues.
• Work with project managers to ensure that projects proceed on time and on budget.
• Collaborate with Technical Product Managers to ensure proper tracking of algorithmic performance KPIs and prioritize performance improvements based on effort and impact.
• Complete other responsibilities as assigned.

Basic Qualifications

• 3-5 years' post-secondary education or relevant work experience

++Additional Qualifications and Skills++

Other Required Qualifications:

• 3-5 years' post-secondary education or relevant work experience
• Bachelor's degree in mathematics, physics, computer science, engineering, statistics, or an equivalent technical discipline.
• 3-5 years' software development experience with Python and SQL.
• 2-3 years' experience in developing and deploying machine learning systems into production in a cloud environment.
• Minimum of two years' experience testing, maintaining, or launching software products and minimum of one year of experience with software design and architecture.
• Experience working with a variety of relational SQL and NoSQL databases, big data tools: Hadoop, Spark, Kafka; a Linux environment; and at least one cloud provider solution (AWS, GCP, Azure).
• Knowledge of data pipeline and workflow management tools.
• Expertise in standard software engineering methodology, e.g., unit testing, test automation, continuous integration, code reviews, design documentation.