Machine Learning Engineering Manager
HybridBudapest, Budapest, Hungary
Job Summary
Lead and grow the team by guiding career development, mentoring engineers, and managing conflicts across a geographically distributed organization. Run a portfolio of experiments rather than a delivery queue, partnering with tech leads to pressure-test hypotheses and make resource decisions on which bets get compute and headcount. Manage the trade-off between committed improvement targets and long-horizon research, re-cutting budgets as evidence arrives to explain reasoning to stakeholders. Bring rigor to offline results predicting online behavior, ensuring independent workstreams converge into release candidates that ship or are cut if they don't carry their weight. Set direction from data in partnership with Risk partners, operating with high autonomy to defend team priorities without waiting for a product backlog. Represent team results to engineering leadership, Risk leaders, and the wider company while partnering on feature systems and experimentation tooling boundaries.
Required Qualifications
- Roughly 5+ years in machine learning, data science, or ML-adjacent software engineering
- At least 3 years of people management
- Guiding career development
- Addressing conflicts
- Building a healthy, high-performing team
- Genuine depth in at least one of engineering and applied statistics
- Real working competence in the other
- Demonstrated ability to lead work under real uncertainty
- Setting a direction when the answer isn't known yet
- Changing course when evidence says to
- Communicating without eroding your team's confidence
- Excellent written and verbal communication
- Autonomy in recognizing priorities and evaluating the impact of outcomes
- Comfort working without close supervision in a fast-moving environment
- Commitment to quality
- Pride in work that excels in correctness, reproducibility, and reliability
- Setting that standard for your team
- #LI-Hybrid
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