Machine Learning Engineer H / M

We are seeking a skilled and strategic Data Scientist to take ownership of our machine learning projects on the Google Cloud Platform (GCP). The ideal candidate is a hands-on expert in data science who also possesses a strong ability to bridge the gap between technical teams and business stakeholders.

You will be responsible for the entire lifecycle of data science projects, from conceptualization and stakeholder communication to model development, deployment on GCP, and performance monitoring. You will be expected to bring a senior-level perspective to the team and help set the standard for analytical excellence within the company.

Project Leadership & Mentorship : Drive data science projects from inception to deployment, providing technical guidance and mentorship to other team members.

Business Communication : Act as the primary point of contact between the data science team and business units. Translate business challenges into data science problems and clearly communicate complex technical results and their business implications to non-technical stakeholders.

Architect, build, and deploy scalable machine learning models and data-driven solutions using Google Cloud Platform services (e.g., Vertex AI, BigQuery, Cloud Storage, Dataflow).

Write high-quality, production-ready code in Python for data analysis, feature engineering, model training, and evaluation.

Project Management : Define project scopes, timelines, and deliverables. Manage project priorities and ensure the timely delivery of high-impact solutions.

Technical Strategy : Stay current with the latest advancements in machine learning, AI, and Google Cloud technologies, and drive the adoption of best practices in MLOps and data science.

A strong track record of successfully leading complex data science projects from concept to production.

Google Cloud Expertise : Demonstrable, hands-on experience with the GCP data and ML stack. Vertex AI (Pipelines, Training, Endpoints)

BigQuery & BigQuery ML

Cloud Storage, Pub / Sub, Dataflow / Dataproc

Expert-level programming skills in Python and proficiency with data science libraries (Pandas, NumPy, Scikit-learn, etc.).

Strong experience with deep learning frameworks such as TensorFlow or PyTorch.

Solid understanding of machine learning algorithms (e.g., Demonstrated experience in managing the full lifecycle of a data science project.

Google Cloud Professional Machine Learning Engineer or Professional Data Engineer certification.

Terraform).

Experience working in an Agile / Scrum development environment

Izertis, with more than 28 years of experience, listed on the BME Continuous Market and among the 1,000 fastest growing companies among European countries, gives you the opportunity to develop your career with more than 2,300 employees through its offices in Europe, America and Africa and with presence in more than 50 countries where we provide services and projects through a broad portfolio of solutions.