Remote Co-op Data De-identification Engineer

Tonic.ai; United States; Remote; USD 34,000 - 55,000; Part time

Job summary

Tonic.ai is seeking a thoughtful software engineer for a remote co-op role (~20 hours/week). You’ll own the delivery of client de-identification projects, run our de-identification pipeline, and work with an engineering and data science team to ship usable datasets for AI labs.

You’ll diagnose issues, fix them, and turn one-off fixes into reusable tooling and runbooks. Current students welcome; prior data engineering experience is a plus, but curiosity and rigor are essential.

Qualifications

• Bachelor’s degree in a technical field or current enrollment.
• Experience shipping production data systems.
• Proficient in Python and SQL.
• Experience building data pipelines.
• Familiar with AI-native workflows.
• Strong self-direction and communication.

Responsibilities

• Own the delivery of client de-identification projects from initial data review to client-accepted dataset.
• Run each corpus through the de-identification pipeline and check output for accuracy.
• Diagnose problems and fix them where possible, or explain to the engineer who can.
• Rerun the pipeline, confirm the fix, then proceed to the next steps with annotation teams.
• Build and adjust ingestion/transformation steps turning raw exports into processed datasets.
• Write code for merging into the platform with client-specific handling.
• Run reconciliation checks ensuring ingest-to-delivery data consistency.
• Contribute to client report sections detailing data handling and limitations.
• Guide clients through the data and results with founders present or independently.

Skills

Python

Backend programming

SQL

Data engineering

Pipeline development

AI-native workflow

Communication

Self-direction

Time management

Education

Bachelor's degree in CS/Engineering/Math/Statistics/Physics or related field

Currently enrolled student

Job description

Tonic.ai is seeking a thoughtful software engineer for a remote co-op role (~20 hours/week). You’ll own the delivery of client de-identification projects, run our de-identification pipeline, and work with an engineering and data science team to ship usable datasets for AI labs.

You’ll diagnose issues, fix them, and turn one-off fixes into reusable tooling and runbooks. Current students welcome; prior data engineering experience is a plus, but curiosity and rigor are essential.