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We are seeking a highly skilled MLOps Engineer to join our Quality Analytics Team at Ford Motor Company. As a key member of our team, you will be responsible for transitioning new machine learning models from proof of concept to production, ensuring scalability, reliability, and efficiency.
Key Responsibilities- Collaborate with the modeling team to facilitate the smooth transition of new models from proof of concept to production, leveraging Google Cloud Platform services.
- Design and develop a robust back-end infrastructure to deploy machine learning models in real-time streaming contexts.
- Develop ETL pipelines to ensure seamless data integration and processing for model training and inference.
- Work closely with the data engineering team to optimize and streamline data pipelines and workflows.
- Stay up-to-date with the latest advancements in MLOps and implement best practices to enhance model deployment and monitoring.
- Collaborate with cross-functional teams to ensure the successful integration of ML models into production systems.
- Bachelor's degree in computer science or a related field.
- 1+ year of experience working with Google Cloud Platform services, leveraging its capabilities for ML model deployment.
- 2+ years of experience in Python programming, including libraries such as TensorFlow, PyTorch, or scikit-learn.
- 2+ years of experience in Java programming.
- Master's degree in computer science or a related field.
- Proficiency in writing and maintaining ETL pipelines, extracting data from various sources and transforming it for model training and inference.
- Familiarity with Apache Beam for building data processing pipelines.
- Experience with Git and GitHub for version control and collaboration.
- Previous experience working in a large, data-driven organization, with exposure to complex analytics workflows and data systems.
- Strong communication skills, with the ability to effectively collaborate with cross-functional teams and stakeholders.
