Machine Learning Engineering Manager
A Machine Learning Engineering Manager at Signifyd leads a team in the AI Lab, building ML products for fraud and risk decisions in e-commerce. The role involves managing a geographically distributed team, running experiments to improve predictive models, setting direction with data, and partnering with risk teams. Core responsibilities include technical mentorship, prioritizing research bets, and
- Compensation
- Not disclosed
- Location
- Budapest, Hungary;
- Work setup
- Not specified
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- 3+ years
- Category
- Ml / AI
- Posted
Skills
Must have
- 5+ years in machine learning, data science, or ML-adjacent software engineering, including at least 3 years of people management
- Depth in at least one of engineering and applied statistics, and real working competence in the other
- Demonstrated ability to lead work under real uncertainty
- Excellent written and verbal communication
- Autonomy in recognizing priorities and evaluating impact
- Commitment to quality (correctness, reproducibility, reliability)
- Candidates must be based in Hungary
Full description
At Signifyd, we help merchants confidently grow their businesses by building trusted relationships with their customers. Our advanced technology, combined with a team genuinely invested in our clients’ success, creates frictionless shopping experiences, approving more good orders, protecting revenue, and keeping customers happy.
Trusted by thousands of leading merchants across more than 100 countries, we securely process billions of transactions each year. Our people are the heart of everything we do, driving our mission forward with commitment, empathy, and creativity. Join us on our mission to empower confident, fraud-free commerce by helping online retailers provide superior customer experiences and eliminate fraud. Learn about our company values here!
ML Engineering Manager
Department: AI Lab/Machine Learning
Signifyd AI Lab (SAIL) builds the ML products behind Signifyd's fraud and risk decisions. We improve the predictive performance of the models that decide e-commerce transactions at scale, we scale the ML capabilities of our Risk organization, and we push into the new markets and problem spaces that expand the market Signifyd can sell to.
Every space in this department is a mix of experimentation, code, and statistics. We don't create walls between the people who have the ideas and the people who build them. The team splits its time between near-term continuous model improvements and longer-horizon innovation bets to improve the company’s capabilities in 2027 and beyond. These bets surface from the ground up in an environment where we believe those closest to the problems are best placed to understand how to solve them.
We’re hiring a manager to lead one of the teams in this department.
Who You Are
You are a hands-on Player-Coach who thrives in ambiguity—where the roadmap is a set of hypotheses, and the answer to "will this work?" is "we'll know in three weeks."
You bring:
Technical Credibility (The "Player"): You stay close enough to the work to have a grounded opinion. You read the code, inspect evaluation pipelines, and can immediately tell the difference between a statistical result that will hold up in production and one that just happened to look good on a single test window.
Leadership & Rigor (The "Coach"): You hold a high bar for evidence without becoming a bottleneck to experimentation. You mentor engineers to own their code quality, and you translate complex ML performance metrics into clear business outcomes for Risk leadership.
Executive Judgment: You know how to balance research bets against quarterly delivery, disagree and commit when decisions are made, and build an environment where well-documented negative experimental results are celebrated as real progress.