Machine Learning Ops Engineer
McDonald's new growth strategy, Accelerating the Arches, encompasses all aspects of our business as the leading global omni-channel restaurant brand. As the consumer landscape shifts we are using our competitive advantages to further strengthen our brand. One of our core growth strategies is to Double Down on the 3Ds (Delivery, Digital and Drive Thru). McDonald's will accelerate technology innovation so 65M+ customers a day will experience a fast, easy experience, whether at one of our 25,000 and growing Drive Thrus, through McDelivery, dine-in or takeaway.
Leading this tech revolution is McDonald's Global Technology organization made up of intrapreneurs who get to build really cool tech with scary smart people using the latest innovations like AI, IOT, and edge computing. We do this working along diverse, global teams who are always hungry for a challenge. It's bonus points when you get to see your family and friends use the tech you build at their favorite McD restaurant.
As we have matured as an engineering organization and seen the demands for technology grow exponentially, we're gearing up to deliver on the next set of opportunities for the business. We are building up an engineering team in house accountable for our strategic products. We'll have diverse squads made up of engineers with traditional and specialized skillsets, both from internal engineers coupled with our partners, to help us flex with demand and solve technology innovation challenges done at an incredible scale.
As Machine Learning Ops engineer in our Global Technology Data & Analytics team, you'll be working with an outstanding global team of data engineers, data scientists and other product managers to build cutting edge analytics solutions and applications. It is an exciting time at McDonald's as we are growing our analytics and ML engineering capabilities and team.
What you will do?
- Design, build and the ML Ops framework and set up cloud platform components for data science models to deploy, scale and ensure ongoing monitoring
- Develop CI/CD pipeline and automation for data ingestion and model deployment
- Collaborate with data scienstists, data engineers and architects to define and implement technical architecture blueprint for AI/ML solutions
- Build and maintain tools and infrastructure for data processing for AI/ML development initiatives
- Develop and update technical documentation for senior leaders and colleagues to serve as a reference guide.
Must have received or be willing to receive the COVID-19 vaccination by date of hire to be considered. Proof of vaccination required.
- 3+ years in DevOps, Data Engineering and ML background with Cloud platforms
- 3+ years of experience with MLOps tools such as MLFlow and Kubeflow
- 3+ years of experience in Python scripting and analytics platforms like Databricks or Sagemaker
- Bachelor's degree in engineering, statistics, or other field with a quantitative component is required; Master's degree preferred.
Strongly Preferred Skills:
- Hands-on experience with modern machine learning libraries, frameworks, and technologies
- Ability to leverage critical thinking and analytical skills to improve business outcomes
- Excellent written and verbal communication skill
- Self-motivated with ability to set priorities and mentor others in a performance driven environment.
- Experience with continuous integration and deployment (CI/CD) frameworks.
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