Data Engineer with ML Exp

Role: Data Engineer with ML Exp

Location : Remote.

Type: Fulltime

Job Summary

A Data Engineer with Machine Learning (ML) experience is a specialized role that combines data engineering skills with the ability to implement and manage machine learning models. Here are some key responsibilities and skills typically associated with this role.

Responsibilities

• Data Pipeline Development: Design, build, and maintain scalable data pipelines to support machine learning workflows.
• Data Integration: Integrate data from various sources, ensuring data quality and consistency.
• Model Deployment: Deploy machine learning models into production environments, ensuring they are scalable and reliable.
• Collaboration: Work closely with data scientists, machine learning engineers, and other stakeholders to understand data requirements and deliver solutions.
• Performance Optimization: Optimize data processing and machine learning model performance.
• Monitoring and Maintenance: Monitor data pipelines and machine learning models to ensure they are functioning correctly and efficiently.

Years of experience needed

• 7 + Years of Experience

Technical Skills:

• Programming: Proficiency in languages such as Python, Java, and SQL.
• Data Engineering Tools: Experience with tools like Apache Spark, Hadoop, and Kafka.
• Machine Learning Frameworks: Familiarity with ML frameworks such as TensorFlow, PyTorch, or scikit-learn.
• Cloud Platforms: Experience with cloud services like AWS, Google Cloud, or Azure.
• Database Management: Knowledge of both SQL and NoSQL databases.
• Data Visualization: Ability to create visualizations to communicate data insights effectively.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.