Data Engineer Intern: AI Medical Imaging Pipelines

VoxelCloud; Los Angeles (CA); On-site; USD 34,000 - 55,000; Part time

Benefits offered by this job

Transparent environment

Competitive compensation

Medical coverage

401k + PTO

Job summary

VoxelCloud, a Los Angeles-based leader in AI analysis of medical images, seeks a Data Engineer intern to help build and optimize data pipelines supporting ML research. You will work with medical data across modalities, focusing on scalable infrastructure and secure data handling.

The role reports to the Data Team Lead and emphasizes hands-on data engineering, cloud-based solutions, and collaboration with software and ML engineers on product initiatives.

Qualifications

• Pursuing an MS/BS in computer science, statistics or a related field.
• Proficient in at least one OO scripting language (Python, Java, C++, Scala).
• Working SQL knowledge; familiarity with PostgreSQL or similar databases.
• Experience building/big data pipelines, scalable data sets, and data architectures.
• Knowledge of AWS cloud services (EC2, EMR, RDS, Redshift) is a plus.

Responsibilities

• Create and maintain optimal data pipelines to support ML research and development.
• Identify and implement internal process improvements: automate data QA, optimize delivery, and redesign infrastructure for scalability.
• Build ETL pipelines using SQL and cloud big data technologies.
• Develop analytics tools to extract insights on product usage and operational efficiency.
• Ensure data is kept secure and separated across national boundaries.

Skills

Python

Java

C++

Scala

Education

MS/BS in CS or related field

Statistics

Tools

AWS

PostgreSQL

SQL

Redshift

DFS

Job description

VoxelCloud, a Los Angeles-based leader in AI analysis of medical images, seeks a Data Engineer intern to help build and optimize data pipelines supporting ML research. You will work with medical data across modalities, focusing on scalable infrastructure and secure data handling.

The role reports to the Data Team Lead and emphasizes hands-on data engineering, cloud-based solutions, and collaboration with software and ML engineers on product initiatives.