We are seeking an experienced Machine Learning Engineer with a strong background in Azure Machine Learning and big data technologies. This role focuses on leveraging advanced statistical methods and machine learning techniques to deliver impactful predictive analytics projects.
Key Responsibilities
- Statistical Analysis. Conduct advanced statistical analyses to support data-driven decision-making.
- Predictive Modeling. Develop and implement predictive models using machine learning techniques.
- Machine Learning. Utilize Azure Machine Learning for building and deploying machine learning models.
- Deep Learning. Apply deep learning frameworks such as TensorFlow, Keras, and PyTorch for complex problem-solving.
- Learning Techniques. Employ supervised and unsupervised learning methods to extract insights from data.
- Programming Skills. Proficient in Python and SQL, leveraging libraries such as Pandas, NumPy, Scikit-learn, and Matplotlib for data manipulation and visualization.
- Azure Ecosystem. Work extensively with Azure services, including Azure ML, Synapse Analytics, SQL Database, and Data Lake Storage.
- Big Data Technologies. (Good to have) Experience with tools like Apache Hadoop, Spark, and Kafka, and familiarity with Azure HDInsight, Synapse Analytics, and Databricks.
- Project Execution. Lead end-to-end predictive analytics projects using Azure, focusing on predictive maintenance and industry applications.
Qualifications
- Experience. 5+ years in machine learning and data analysis.
- Strong proficiency in Python and SQL.
- Experience with Azure ML and related Azure services.
- Familiarity with deep learning frameworks such as TensorFlow, Keras, and PyTorch.
- Experience with big data technologies, including Apache Hadoop, Spark, and Kafka.
Application Process. If you are a passionate Machine Learning Engineer with a focus on predictive analytics and Azure technologies, we encourage you to apply. Please send your CV to [email protected].
Join ValueLabs to be part of a forward-thinking team that is dedicated to leveraging technology for impactful solutions!