Software engineer senior H/F (IT)

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.
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.
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 bring strong engineering fundamentals and collaborate naturally, helping the team converge on quality decisions. Build , optimize, and embed machine learning models for on-device inference within the QSIDS detection engine.
Optimize models for performance and resource constraints, minimizing memory footprint, latency, and compute on-device.
Take models all the way to production and own them once they're running, monitoring performance, detecting drift, and iterating to keep them reliable.
Stay on the lookout for the latest ML and other technologies and best practices - but resist novelty chasing.
Help onboard and train colleagues as the team grows.
Effectively communicate technical concepts to both technical and non-technical stakeholders.
7+ years' experience building and shipping machine learning models to production- including deploying, running, and monitoring them in live environments

• Hands-on track record owning models post-deployment: monitoring performance, detecting drift, and iterating on production systems
• A bachelor's or master's degree in computer science, engineering, or a related field (or equivalent professional experience)

Experience embedding ML models for on-device inference (a strong asset for this role)
Experience with high-performance, low-resource systems programming (memory management, multithreading, optimization), ideally in Go or an adjacent systems language
Bilingual (French and English)
Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
Competitive salary range.
Life insurance
Short- and long-term disability
Health Spending Account (HSA)

All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, colour, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by applicable law. A working proficiency in English is required for this position based on the company's operational requirements.