Senior Machine Learning Developer

Qohash is building the zero copy data security control layer, enterprises need to adopt AI safely.

Our platform, Qostodian, helps large organizations discover, classify, govern, and remediate sensitive unstructured data across their most critical data sources without moving or copying the data.

This zero copy architecture reduces exposure, preserves data sovereignty, and allows enterprises to secure data directly where it lives.

This matters because AI adoption is increasing the risk, complexity, and urgency of enterprise data security.

Before organizations can safely deploy AI agents, copilots, retrieval systems, or automated workflows, they need to know where sensitive data lives, who and what can access it, and how to enforce controls at scale.

Company culture is at our core

Our 5 core values are more than just words, they are a way of life for us.

We know that companies with a strong culture and a higher purpose perform better in the long run.

Do our values speak to you?

• Pursuit of excellence
• Resilience
• Mission focus
• Accountability
• Embracing conflict

About the team

We are standing up a new team for the QSIDS (Qohash Sensitive Information Detection System) launch, dedicated to the detection engine .

A central focus of this team is the integration of embedded AI , machine learning models that run directly on the device and in-system.

It is about high-performance, low-resource, on-device inference, embedded into the detection engine itself.

The engine is built in Go , with a strong emphasis on performance and minimal resource footprint.

Who you are

You're a hands-on machine learning developer who's energized by getting models out of the notebook and into the real world, shipped, running, and holding up under production conditions.

You take pride in owning what you build: watching how your models behave once deployed and iterating to keep them sharp.

You bring strong engineering fundamentals and collaborate naturally, helping the team converge on quality decisions.

You're comfortable with the pace and ambiguity of a startup, and you care about the outcome, not just the code.