Intern Machine Learning Operations

Stellantis is a leading global automaker and mobility provider that offers clean, connected, affordable and safe mobility solutions. Our Company’s strength lies in the breadth of our iconic brand portfolio, the diversity and passion of our people, and our deep roots in the communities in which we operate. Our ambitious electrification and software strategies and the creation of an innovative ecosystem of strategic, game-changing partnerships are driving our transformation to a sustainable mobility tech company. The driving force behind us is the diverse and talented group of men and women around the world who bring their passion and experience to their work every day. And while we are a truly global organization, we remain deeply rooted in the communities in which we operate and where our colleagues live and work. With industrial operations in nearly 30 countries, Stellantis could consistently exceed the evolving needs and expectations of consumers in more than 130 markets, while creating superior value for all stakeholders. **Please submit your CV in English.** **Your Mission** The Artificial Intelligence and Data Analytics Team is looking for a **Machine Learning Operations Intern** to support the development of monitoring and observability tools for production machine learning and data pipelines. During the internship you will work closely with Machine Learning Engineers and Data Scientists to improve the transparency and operational stability of our ML systems. You will play a vital role in supporting the development and deployment of machine learning models, ensuring they run smoothly in production environments. You will work closely with data scientists and engineers to streamline the machine learning lifecycle, from model training to deployment and monitoring. **Your Responsibilities** * Support the development of monitoring and observability tools for production ML and data pipelines * Model Deployment and Monitoring: Assist in deploying machine learning models to production environments, ensuring they are scalable and reliable. * Help design and implement dashboards presenting the health and performance of workflows running on Databricks * Work with the team to implement version control and collaboration best practices for machine learning projects, using tools like Git * Contribute to building centralized dashboards in tools such as Grafana or Microsoft Power BI * Assist in implementing monitoring logic for detecting failures and anomalies in ML pipelines * Work with ML engineers and data scientists to improve the reliability of production and development systems * Support the development of internal team templates and standards. **Top Performers will be able to demonstrate** * Curiosity about how machine learning systems operate in production and development environments * Ability to analyze pipeline execution data and identify potential issues or inefficiencies * Strong problem-solving mindset and attention to detail * Ability to collaborate with Data Scientists, ML Engineers and Platform teams * Willingness to learn modern Machine Learning, Data engineering and MLOps practices and technologies * Proactive attitude and eagerness to contribute ideas and improvements **Skills** * Currently pursuing or recently completed a degree in Computer Science, Data Science, Statistics, Engineering or a related STEM field * Good knowledge of **Python** * Basic knowledge of **SQL** * Familiarity with **Git** and collaborative development workflows * Understanding of fundamental **machine learning and data processing concepts** * Ability to work with data and analyze results * Working proficiency in **English** * Effective communication skills and the ability to work collaboratively in an international team environment **Extra points for** * Experience with Python data libraries (Pandas, NumPy, Scikit-Learn) * Basic experience with **machine learning model development and experimentation** * Familiarity with ML lifecycle tools such as mlflow * Exposure to machine learning frameworks such as TensorFlow or PyTorch * Basic knowledge of Apache Spark / PySpark * Experience with data visualization or dashboarding tools (e.g. Grafana or Microsoft Power BI) * Exposure to cloud platforms such as AWS * Familiarity with Linux-based operating systems and command-line tools * Interest in **MLOps, ML infrastructure, or production machine learning systems** *At Stellantis, we assess candidates based on qualifications, merit and business needs. We welcome applications from people of all gender identities, age, ethnicity, nationality, religion, sexual orientation and disability. Diverse teams will allow us to better meet the evolving needs of our customers and care for our future.*