Senior Machine Learning Engineer

STAFIDE; Amsterdam; On-site; EUR 110,000 - 150,000; Full time

Job summary

STAFIDE is seeking a Senior Machine Learning Engineer to design, develop, and deploy ML solutions that address complex business challenges in Amsterdam. You will build scalable data processing pipelines using Python and SQL to support predictive analytics and data-driven decisions.

You will work with cloud-based platforms (Azure, AWS, GCP) and collaborate with cross-functional teams to translate requirements into robust AI/data science solutions, continuously improving model performance and code

Qualifications

• Experience designing, developing and deploying ML solutions for business problems.
• Proficient Python development with data science libraries (Pandas, NumPy, scikit-learn).
• Strong SQL skills and experience on enterprise platforms (BigQuery, Teradata).
• Hands-on with cloud ML platforms (Azure, AWS, GCP).
• Solid understanding of ML model training, evaluation, and feature engineering.
• Ability to analyze and transform large structured/unstructured datasets.
• Excellent communication and cross-functional collaboration.
• Experience with scalable data processing pipelines and documentation.

Responsibilities

• Design and deploy end-to-end ML solutions for business problems.
• Build scalable data processing pipelines using Python and SQL.
• Develop and validate ML models for predictive analytics and decisions.
• Clean and transform large datasets for model development.
• Leverage cloud platforms and notebooks for ML workflows.
• Collaborate with data engineers, analysts, and stakeholders.
• Improve model performance through feature engineering and evaluation.
• Document code and create reusable workflows for reuse.
• Support deployment, monitoring, and maintenance in the cloud.
• Stay updated with ML/cloud best practices.

Skills

Python

Data Science

ML/Algorithms

SQL

Cloud Platforms

R

BigQuery

Teradata

Model Evaluation

Communication

Education

Bachelor’s or Master’s in CS/Statistics

Tools

Azure ML Studio

Azure Databricks

AWS

GCP

Python Libraries (Pandas, NumPy, scikit-learn)

Job description

As a Senior Machine Learning Engineer, you will:

• Design, develop, and deploy machine learning solutions to solve complex business problems.
• Build scalable data processing and analytics solutions using Python and SQL.
• Develop statistical and machine learning models to support predictive analytics and data-driven decision-making.
• Analyze, clean, and transform structured and unstructured datasets for model development.
• Work with cloud-based analytics and machine learning platforms, including Azure Machine Learning Studio, Azure Databricks, AWS, and Google Cloud Platform (GCP).
• Collaborate with cross-functional teams to understand business requirements and translate them into scalable AI and data science solutions.
• Optimize model performance through feature engineering, model evaluation, and continuous improvement.
• Develop reusable data science workflows and maintain high standards for code quality and documentation.
• Support deployment, monitoring, and maintenance of machine learning solutions in cloud environments.
• Stay updated with emerging technologies and best practices in machine learning, cloud computing, and data engineering.

What You Bring to the Table:

• 8–10 years of professional experience in Python development, Data Science, Machine Learning, or Analytics Engineering.
• Strong programming expertise in Python with hands-on experience using Scikit-learn, Pandas, NumPy, Matplotlib, statsmodels, and related data science libraries.
• Working knowledge of R for statistical computing and data analysis.
• Strong SQL skills with experience working on enterprise data platforms such as Teradata and BigQuery.
• Solid understanding of machine learning algorithms, model training, validation, and evaluation techniques.
• Experience in statistical analysis, predictive modeling, and data exploration.
• Familiarity with cloud-based analytics and machine learning platforms, including Azure Machine Learning Studio, Azure Databricks, Google Cloud Platform (GCP), and Amazon Web Services (AWS).
• Experience working with large datasets and designing scalable analytics solutions.
• Strong analytical, problem-solving, and communication skills.
• Ability to quickly learn new technologies and adapt to evolving business requirements.

You Should Possess the Ability to:

• Design and implement end-to-end machine learning solutions.
• Develop scalable data processing pipelines and analytical models.
• Apply statistical techniques to extract meaningful business insights.
• Build, evaluate, and optimize machine learning models using industry best practices.
• Work with cloud-native machine learning and analytics platforms.
• Analyze large and complex datasets using SQL and Python.
• Collaborate effectively with data engineers, analysts, architects, and business stakeholders.
• Troubleshoot technical issues and optimize model performance.
• Communicate technical concepts clearly to both technical and non-technical audiences.
• Deliver high-quality solutions while maintaining a strong focus on accuracy, scalability, and continuous improvement.

What We Bring to the Table:

• Opportunity to work on enterprise-scale data science and machine learning initiatives.
• Exposure to modern cloud platforms, advanced analytics, and AI technologies.
• A collaborative environment focused on innovation, continuous learning, and technical excellence.
• Opportunities to work with experienced engineers, data scientists, and cloud architects.
• Challenging projects involving Python, cloud-native machine learning, statistical modeling, and enterprise analytics.
• A culture that encourages ownership, knowledge sharing, and professional growth.
• Continuous opportunities to enhance expertise in cloud comp uting, machine learning, and advanced data engineering.