Plata
Cyprus
Principal Research Scientist - Risk (AI/ML)
Machine Learning Full-time Mid-Senior level 20h ago
- AI
- Deep Learning
- Machine Learning
AI Summary
Lead a cross-functional engineering team that turns business and product hypotheses into production AI features. Own delivery end to end, partner with Product, Data, and AI, and shape scalable backend services and integrations. Requires hands-on engineering leadership experience in AI, ML, or data-driven environments and the ability to validate technical decisions independently.
Key Highlights
Hands-on engineering leadership for AI business features
Own delivery end to end across a broad portfolio of initiatives
Partner with Product, Data, and AI on scope and prioritization
Shape architecture and scalable backend services and integrations
Relocation support to Cyprus, Spain, or Georgia hubs
Key Responsibilities
Lead the team across hiring, planning, task decomposition, process improvements, and cross-team collaboration
Own and drive the development of AI-powered products from concept to production
Ensure strong team performance and reliable, on-time delivery aligned with product and business goals
Partner closely with Product, Data, and AI teams to build impactful, user-centric solutions
Tackle complex technical and product challenges while maintaining high engineering quality standards
Shape the architecture, design, and implementation of scalable backend services and integrations
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Technical Skills Required
Benefits & Perks
Relocation support
Flexible work from office or remote
Healthcare Coverage
Education Budget
Wellness Budget
Vacation Policy
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Nice to Have
Experience training models
Job Description
We are looking for a hands-on Engineering Manager for AI Business Features - the team that turns business and product hypotheses into production AI features. You will lead a cross-functional engineering team, own delivery end to end, and work directly with Product, Data, and AI on scope and prioritization. The role requires enough technical depth to review architecture and challenge design decisions yourself, not through a proxy.
The team works in short cycles: hypotheses go to production, get measured, and are then scaled or dropped. Expect a broad portfolio of initiatives rather than one long-running product.
Challenges that await you:
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