Senior Machine Learning Engineer
Job Location:
Amsterdam - Netherlands
Monthly Salary:
Experience Required:
Posted:
Application Deadline:
Vacancies:
Job Summary
- 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.
- 810 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.
- 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.
- 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 computing machine learning and advanced data engineering.
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: 810 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 computing machine learning and advanced data engineering. Lets Connect Want to discuss this opportunity in more detail Feel free to reach out. Recruiter: Giftson Paul Davidson Phone:; Extn : 151 E-mail: LinkedIn:
