As an ML / Data Science Engineer, you will manage and enhance the automated AWS pipeline that processes data from our sensors and mobile applications. Your work will be critical in extracting insights and guiding our customers’ sustainability strategies. Currently, our technology is deployed in three regions, collecting live data from thousands of monitored stations.

Key responsibilities include:

• Data Engineering: Maintain and evolve the AWS-based pipeline infrastructure (Glue, Athena, SageMaker) for analyzing live sensor and image data.

• Data Analytics: Use the infrastructure to track waste generation, detect anomalies, assess interventions, and visualize waste metrics across various levels.

• Computer Vision: Improve our AI model for automated waste identification

• Standardization: Propose methods to standardize data across customers for comparison and benchmarking.

• Model Development: Explore ML models to predict the impact of specific waste management initiatives.

• Visualization: Create interactive data visualizations to support customer decision-making processes.

We are looking for candidates with the following skills and attributes:

• Education: Engineering degree or PhD in a relevant field (e.g., Data Science, Computer Vision).

• Technical Expertise: Strong background in Data Engineering, Data Science, and Computer Vision, particularly in object identification and instance segmentation (YOLOv8 preferred).

• Programming Skills: Proficiency in Python, Spark, and SQL.

• Cloud Platforms: Experience with AWS services (Glue, Athena, S3, QuickSight preferred).

• Problem Solving: Excellent analytical and problem-solving skills.

• Teamwork: Strong communication skills and the ability to work effectively in a team.

• Organizational Skills: Well-versed in Agile methodologies, Scrum, source code management, CI/CD processes, and testing.

• Passion: A genuine passion for data science and making a positive impact through technology.

The selection process includes an initial screening, followed by a general interview with our CTO (conducted in French). Shortlisted candidates will then proceed to a technical interview with members of the R&D team.