Data Engineer (Remote in Colorado)

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Requirements:

• 5+ years of Python experience.
• 3+ years leveraging technologies such as Airflow and Apache Spark.
• Experience working with large language models, diffusion models, or other generative models.
• Experience with MLOps tools and practices.
• Strong understanding of data architectures and patterns.
• Experience with containerization technologies like Docker and Kubernetes.
• Contributions to open-source projects.
• Experience in DataOps and MLOps implementation and support.
• Experience in building and supporting AI/ML platforms.

Responsibilities:

• Design, develop, and maintain robust, scalable data pipelines for processing large datasets for AI model training.
• Perform data cleaning, normalization, transformation, and feature engineering, including handling unstructured data.
• Build and manage data infrastructure like data lakes and warehouses, optimized for AI workloads.
• Implement data quality checks and monitoring systems for data accuracy and consistency.
• Contribute to MLOps best practices for data management and model deployment.
• Work with GCP and Snowflake for data and AI offerings.
• Optimize data pipelines and infrastructure for performance, scalability, and cost-effectiveness.