TL;DR

Senior Data Engineer (Machine Learning): Build and maintain scalable data infrastructure and detection models to identify and mitigate fraud and abuse. Focus on architecting data solutions, improving ML-based threat detection, and ensuring system reliability at scale.

Location: Hybrid work with regular presence in London office (2x per week)

Company

%hirify_global% is a global communications platform powered by Language AI, focused on breaking down language barriers and enabling better communication worldwide.

What you will do

Architect and build scalable data infrastructure for fraud and abuse detection.
Power and refine machine learning detection models to identify suspicious activity.
Ensure reliability and availability of data pipelines and detection tools at scale.
Collaborate with backend engineers and other teams to integrate defenses like rate limiting and bot protection.
Champion data excellence and share expertise within the data community.
Participate in on-call rotation to maintain service reliability.

Requirements

Must be comfortable with hybrid work and able to come to London office regularly.
Professional experience in Python and SQL software development.
Strong foundation in algorithms and data structures.
Practical experience applying machine learning techniques to real-world problems.
Experience with distributed systems, computer networks, and container orchestration.
Effective problem-solving mindset balancing perfection and business impact.

Nice to have

Experience with C# / .NET.

Culture & Benefits

Diverse international team with over 90 nationalities.
Open communication and regular feedback culture.
Hybrid work schedule with flexible hours.
Regular in-person team events and monthly hack days.
30 days annual leave plus mental health resources.
Competitive benefits tailored to global locations.