About the role#
Tonic.ai is looking for a Forward Deployed Engineer to join our data de-identification team. This co-op role focuses on preparing sensitive company data for AI training. You will act as an independent third party between data owners and AI labs, ensuring that sensitive information is protected while maintaining the utility of the data. This is a remote position requiring roughly 20 hours of work per week.
What you'll do#
- Own the delivery of client de-identification projects from initial raw data review through client acceptance.
- Run corpora through the de-identification pipeline and verify output accuracy, including checking for missed entities, incorrect replacements, and files that fail to rebuild.
- Diagnose issues and implement fixes, or provide clear explanations to the engineering team for complex problems.
- Collaborate with the annotation team to validate data quality.
- Build and adjust ingestion and transformation steps for various raw exports such as mailboxes, chat archives, document dumps, ticketing systems, and databases.
- Write code within existing platform guardrails, including custom handling for client-specific cases.
- Perform reconciliation checks to ensure file counts and content align from ingestion to delivery.
- Draft technical sections of client reports detailing sensitive data handling, file-type processing, and project limitations.
- Present work and resulting data to clients, initially with company founders and later independently.
- Convert one-off fixes into reusable documentation, runbooks, and product improvements.
What you'll need#
- Bachelor's degree in a technical field like Computer Science, Computer Engineering, Mathematics, Statistics, Physics, or Biology, or current enrollment in one.
- Hands-on experience in data engineering, backend engineering, or a forward-deployed role shipping production systems for customers.
- Strong proficiency in Python and SQL, with the ability to read and debug existing code.
- Experience building repeatable pipelines for processing large volumes of structured, semi-structured, and unstructured data.
- Ability to track data flow through a system and identify output errors.
- An AI-native workflow where you use AI tools and agents while maintaining oversight on their reliability.
- Self-direction and the ability to make sound decisions independently.
- Clear communication skills for both technical and executive audiences.
- A record of delivering complex projects on timelines measured in days and weeks.
- Availability for roughly 20 hours per week with flexibility to maintain project schedules.
- Preferred: Experience with model inference, ML pipelines, or PyTorch.
- Preferred: Experience with data masking, de-identification, ETL, or synthetic data tooling.
- Preferred: Interest in the frontier AI lab and training-data ecosystem.
- Preferred: Experience at an early-stage company or on a new product line.
Location & details#
- Work Modality: Remote
- Location: United States
- Employment Type: Part-time (co-op)
- Schedule: Approximately 20 hours per week
About Tonic.ai
Tonic.ai produces software for synthetic data generation, de-identification, and subsetting. The company provides tools for developers to create realistic structured and unstructured data for testing and AI model training. Founded in 2018, the firm maintains its headquarters in San Francisco, California. It employs 103 people.
How to get in at Tonic.ai
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