Head of Machine Learning Ongoing Monitoring
Speedinvest is a European venture capital firm that invests from seed to growth stage (Series B to pre-IPO), backing founders with sector-specific expertise and a large network of operational support. It leads the majority of its initial investments and continues to support portfolio companies through multiple follow-on rounds as they scale.
About Speedinvest
Speedinvest is a pan-European venture capital investor with specialist investment teams organized around core sectors including AI & Infra, Climate Tech & Industrial Tech, Deep Tech, Fintech & DeFi, Health & Bio, and Marketplaces & Consumer, alongside a dedicated Growth team writing checks from Series B to pre-IPO. The firm emphasizes leading with conviction and long-term capital from day one, leading 85% of its initial investments, participating in 100+ follow-on rounds each year, and backing 70+ Series A companies over the past four years. Speedinvest works with startup founders across Europe and beyond, providing not just capital but network access and growth support, and counts companies like Bitpanda, Moove, cylib, Tide, Gigs, Upvest, and GoStudent among its portfolio.
Skills
About the Role
You will define and execute a risk engineering strategy that supports compliant growth. You will lead managers and engineers, build scalable risk infrastructure for real-time decisions and fraud prevention, and create self-service risk tools for product, compliance, and operations teams. You will work with legal and compliance experts to uphold regulatory standards and lead data and machine-learning initiatives that improve fraud detection, compliance, and resilience.
Requirements
- 12+ years of engineering experience, including at least 2 years in a senior leadership role
- Experience in fintech or regulated technology environments
- Deep experience in fraud prevention and compliance, including KYC/KYB and AML
- Experience with supervised and unsupervised models, decision trees, neural networks, and Large Language Models
- Hands-on experience with multi-agent orchestration frameworks such as LangGraph and AutoGen
- Understanding of fraud vectors and AML typologies
- Experience detecting deepfakes, synthetic identities, and prompt injection attacks targeting financial systems
- 3+ years building and deploying production-grade risk-scoring environments at scale
- Experience with risk and compliance tooling, including AML, fraud, financial risk, SARs, KYX, and agentic AI detections
- People leadership skills
- Knowledge of cloud-native architectures, microservices, event-driven systems, data platforms, AWS, or GCP
Responsibilities
- Define and execute a risk engineering strategy aligned with long-term growth and compliance goals
- Lead managers and engineers and foster excellence, innovation, user-centric design, and collaboration
- Architect and scale risk systems for real-time decision-making, data management, and fraud prevention
- Develop self-service risk tools for product, compliance, and risk operations teams
- Collaborate with legal and compliance experts to support regulatory standards
- Lead data- and machine-learning initiatives for fraud detection and compliance
Benefits
- Generous annual leave in addition to bank holidays
- Paid maternity, paternity, and adoption leave
- Unpaid and paid sabbatical leave after milestone years
- Private family health insurance with OPD coverage and top-up options
- Accidental and life insurance
- Access to therapy sessions, courses, meditations, and workshops
- Paid volunteering and personal-growth days
- Annual learning and development budget
- Work from abroad for up to 90 days annually
- Home office setup contribution
- Laptop replacement and ownership of the old laptop
- Office snacks, coffee, tea, and lunch, depending on location