ML Engineer

Main responsibilities:

• Participate in the framing, MVP and release phases of AI-oriented products, services and APIs;
• Argue the architecture choices of projects and the AI platform on GCP;
• Contribute to the business value of AI-driven products based on the Data Lake, by setting up end-to-end data processing chains, from ingestion to API exposure and visualization of data and AI/ML solutions;
• Be responsible for the quality of the data transformed in the Datalake, the proper functioning of processing chains and the optimization of the use of cloud resource resources;
• Define and develop the components necessary to orchestrate a machine learning system in production according to MLOPS best practices (data validation, preprocessing, training, model analysis, deployment, monitoring, etc.)
• Propose architecture and development standards;
• To be a force of proposal, innovative and benevolent.

Technical environment:

Google Cloud Platform (BigQuery, PubSub, Dataflow, Vertex AI), Airflow, Terraform, Spark, Scala, Python, Looker, Dataiku, Kubernetes, SQL, Git

Skills:

• Experience in Spark, Scala, Python and ML framework development (Vertex, Tensorflow, Scikit, PyTorch, ...);
• Appetite for data: validation, transformation, analysis, valorization;
• Experience in developing and orchestrating complex ETL chains via Airflow or equivalent;
• Practice of agile methodology (Agile Scrum and/or Kanban);
• Have used cloud services (preferably GCP);
• Ability to communicate in written and oral technical English;
• Be ready to take up the challenges of data with us!!