Description

You will build and maintain the engineering infrastructure required to support enterprise machine learning systems at scale.

Responsibilities

• Design and create data pipelines and engineering infrastructure to support large-scale machine learning systems.
• Convert models developed by data scientists into production-ready machine learning systems.
• Develop and deploy scalable tools and services for machine learning training and inference.
• Apply software engineering rigor and CI/CD automation to machine learning workflows.
• Monitor model performance and troubleshoot errors, bugs, or system failures.

Required Skills

• 5+ years of experience with Python, Pandas, and Spark.
• Experience building large-scale data pipelines.
• Hands-on experience with Seldon, Triton, and Jenkins CI/CD.
• Proven ability to turn research models into production systems.
• Strong understanding of model versioning, measurement, and auditability.
• Ability to interpret model results and relate data to underlying problems.

Preferred Skills

• One year of experience with BigQuery, Hadoop, SQL, Hive, GCP/Azure, Java, or REST.

Key Skills

Education

Any Graduate