Data Engineer – AI/ML Data Infrastructure

Overview:

We’re looking for a Data Engineer to build and maintain the data infrastructure that powers machine learning initiatives. You’ll work at the intersection of software engineering and data science.

Responsibilities:

• Develop and maintain feature stores and ML-ready datasets
• Automate data preprocessing pipelines for ML model training and evaluation
• Collaborate with ML engineers to enable scalable experimentation workflows
• Monitor and improve data reliability, lineage, and reproducibility

Requirements:

• BS/MS in Computer Science, Data Engineering, or similar
• Experience with ML platforms (Databricks, AWS Sagemaker, Vertex AI)
• Strong Python and SQL skills, with familiarity in Spark or Dask
• Experience with Airflow, MLflow, or Kubeflow pipelines
• Solid understanding of MLOps, data validation, and model versioning

Job Category: Data Engineer

Job Type: Full Time

Job Location: Boston

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Responsibilities:

• Develop and maintain feature stores and ML-ready datasets
• Automate data preprocessing pipelines for ML model training and evaluation
• Collaborate with ML engineers to enable scalable experimentation workflows
• Monitor and improve data reliability, lineage, and reproducibility

Requirements:

• BS/MS in Computer Science, Data Engineering, or similar
• Experience with ML platforms (Databricks, AWS Sagemaker, Vertex AI)
• Strong Python and SQL skills, with familiarity in Spark or Dask
• Experience with Airflow, MLflow, or Kubeflow pipelines
• Solid understanding of MLOps, data validation, and model versioning

Job Category: Data Engineer

Job Type: Full Time

Job Location: Boston

Responsibilities:

• Develop and maintain feature stores and ML-ready datasets
• Automate data preprocessing pipelines for ML model training and evaluation
• Collaborate with ML engineers to enable scalable experimentation workflows
• Monitor and improve data reliability, lineage, and reproducibility

Requirements:

• BS/MS in Computer Science, Data Engineering, or similar
• Experience with ML platforms (Databricks, AWS Sagemaker, Vertex AI)
• Strong Python and SQL skills, with familiarity in Spark or Dask
• Experience with Airflow, MLflow, or Kubeflow pipelines
• Solid understanding of MLOps, data validation, and model versioning