Senior Machine Learning Engineer

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.

• 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, Num Py, Matplotlib, stats models, 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 Big Query.
• 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 comp uting, machine learning, and advanced data engineering.