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- Developing, researching and implementing MLOps frameworks, tools and platforms for our Data Science projects
- Designing and implementing infrastructure for machine learning cloud services
- Creating microservices for task-specific AI cloud services
- Implementing solutions for monitoring model performance and triggering alerts
- Enhancing speed of delivery, automating Model Retraining, Model Monitoring, Model Versioning, improving quality/security of code, and optimizing processes
- Collaborating with the data platform team to create a feedback loop and improve the underlying data infrastructure
- Partnering with peers to ensure scalability, business continuity and appropriate turnaround time
- Working on a backlog of activities to raise MLOps maturity in the organization. Evolve our framework as new technologies and techniques emerge
- Proactively introduce a modern, agile and automated approach to Data Science
- Experience in converting data science prototypes for deployment into production purposes
- Record of designing and implementing scalable, performant data and machine learning pipelines, services, and products
- Understanding of distributed data systems and experience in using open source frameworks to build applications
- Be able to communicate collaboratively with Data Scientist, Infrastructure teams and client to understand requirements and scope
- Solid intuition when choosing the right ML/AI approaches to the problems given
- to influence non-technical peers and leadership to deliver substantive change
- for less experienced colleagues and guardian of good standards
- MSc / MEng degree in Statistics, Computer Science, Automatic Control, STEM, Engineering or a related discipline
- Experience, coding in Python or other languages
- Experience in the operationalization of Data Science projects (MLOps) using Databricks+MLFlow,
- Hands-on experience with PySpark and SQL
- Working proficiency in English
- Multidimensional skill set: data science, experimentation, AI, statistics, engineering, etc.
- Experience in front- and backend design and development (leveraging Django, , Streamlit or similar)
- experience with containerization (using Kubernetes, Docker)
- in CI/CD/CT pipeline implementation
- overview of AWS services to design cloud solutions
- knowledge in shell scripting and networking
Senior Machine Learning Engineer - São Paulo, SP, Brasil - Stellantis South America
Descrição
About the job
Your Mission
The Global Analytics & Data Products Team is looking for a Senior Machine Learning Engineer. As a key member of the MLOPS team, your mission is to put science into decision making through machine learning initiatives. Priorities can change in a fast-paced environment like ours, so this role includes, but is not limited to the following responsibilities:
Top Performers will be able to demonstrate
Skills
Extra points for: