Data Scientist Mlops - Naucalpan, México - Ford Motor Company
Descripción
As a MLOps Engineer at Ford Motor Company, you will be an integral part of the Quality Analytics Team within the GDI&A organization.
Your role will involve collaborating with the modeling team to transition new models from proof of concept to production.Additionally, you will be responsible for establishing a robust back-end infrastructure to deploy our machine learning models in Google Cloud Platform.
We are seeking a talented individual who possesses a combination of technical skills, industry experience, and effective communication abilities.Responsibilities:
- Collaborate with the modeling team to facilitate the smooth transition of new models from proof of concept to production, ensuring scalability, reliability, and efficiency.
- Create a back-end infrastructure that supports the deployment of our machine learning models in real-time streaming contexts.
- Design and develop ETL (Extract, Transform, Load) 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 updated 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 (Machine Learning) models into production systems.
Baseline Requirements:
- Bachelor's degree in computer science or a related field.
3. 2+ years of experience in Python programming, including libraries such as TensorFlow, PyTorch, or scikit-learn.
4. 2+ years of experience in Java programming
Preferred Requirements:
- 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.
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