Privacy ML Engineer — DP & Federated Learning

Meramia Technologies; Dubai; Remote; AED 300,000 - 540,000; Full time

Job summary

Meramia Technologies in Dubai seeks a researcher-strong ML privacy engineer to prototype and land privacy-enhancing algorithms such as differential privacy, secure aggregation, and federated learning on our training and inference stacks.

You will red-team models for membership inference, inversion, and data memorisation, build evaluation suites for ML engineers, and work with research, platform, security, legal and product to embed privacy as a guardrail in code while exploring the

Qualifications

• Proficiency in privacy-preserving ML techniques
• Ability to prototype privacy algorithms in Python
• Experience turning papers into tested modules

Responsibilities

• Prototype privacy-enhancing algorithms on training and inference stacks
• Red-team models for membership inference, inversion, memorisation
• Build evaluation suites for ML engineers across a model life
• Collaborate with research, platform, security, legal and product to embed privacy as guardrails
• Investigate privacy–utility trade-offs: capability, latency and cost

Skills

Python

Differential privacy

Federated learning

DP-SGD

Model red-teaming

Privacy explainability

Tools

PyTorch

JAX

Job description

Meramia Technologies in Dubai seeks a researcher-strong ML privacy engineer to prototype and land privacy-enhancing algorithms such as differential privacy, secure aggregation, and federated learning on our training and inference stacks.

You will red-team models for membership inference, inversion, and data memorisation, build evaluation suites for ML engineers, and work with research, platform, security, legal and product to embed privacy as a guardrail in code while exploring the