Machine Learning Engineer

Job Description

We are looking for a highly skilled Machine Learning Engineer with strong expertise in SQL, Python, data modeling, and machine learning, along with hands-on experience working with Snowflake and AWS services like SageMaker. The ideal candidate will also be proficient in data visualization tools and familiar with big data frameworks. Key Responsibilities: Design, build, and deploy scalable machine learning models using Python and SQL. Work extensively with Snowflakes advanced features for data storage, processing, and ML integrations. Utilize AWS tools, especially SageMaker, for model training, deployment, and monitoring. Develop robust data pipelines and workflows, ensuring accuracy and efficiency. Create dashboards and visualizations to communicate data-driven insights. Collaborate with cross-functional teams including data engineers, product managers, and business analysts. Requirements: Proficiency in SQL, Python, data modeling, and machine learning algorithms. Hands-on experience with Snowflake and AWS SageMaker (or similar cloud-based ML services). Experience with data visualization tools like Tableau, Power BI, or equivalent. Familiarity with big data technologies such as Spark, Hadoop, or Kafka is a plus. Experience with other ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) is welcome. Strong problem-solving skills and the ability to work independently in a remote environment.