Data Engineer
2 weeks ago
In this role, will be working with software and data to drive Generative AI solutions at McDonald's. Generative AI is opening up powerful new capabilities for building enterprise solutions, and you will be able to help advance their implementation and value at McDonald's.
Responsibilities
1. Technical Solution Development:
Design and develop AI-powered solutions using the technical stack on Google Cloud Platform (GCP), including Vertex AI, Gemini models, and Python.
Work extensively with Python, LLM/GenAI frameworks and various AI/ML tools to develop end-to-end solutions.
Developing CI/CD pipelines, containerizing and deploying LLM models on cloud platforms, testing models, and ensuring their ongoing maintenance throughout the ML model lifecycle.
Design and implement ETL/ELT pipelines, with proficiency
Collaborate with Data engineers to implement AI algorithms to solve business problems.
Collaborate with a team to drive Generative AI solutions forward to solve business problems
Design prototypes and proof-of-concepts (POCs) to demonstrate the feasibility and value of solutions.
Research, design, build, and train innovative applications of LLMs that provide architectural solutions for complex real-world problems.
Ensure the scalability, reliability, and performance of the technical solutions to meet the needs of various stakeholders.
2. Performance Monitoring and Optimization:
Monitor the performance of GenAI-powered products and analyze key metrics to assess their impact on Customers, Corporate, Restaurants, and Markets.
Identify opportunities for optimization and improvement based on data-driven insights and user feedback.
Iterate on product features, user experiences, and business processes to continuously enhance the value delivered by GenAI solutions.
3. Business Requirements Analysis:
Work closely with business stakeholders from Customers, Corporate, Restaurants, and Markets to understand their needs, challenges, and opportunities.
Collaborate with cross-functional teams to deploy solutions on major cloud platforms, with a preference for GCP expertise.
Identify key performance indicators (KPIs) and success criteria for evaluating the effectiveness of GenAI-powered products.
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