
Enzo is a B2B PropTech and WaterTech startup offering innovative solutions tailored to the needs of insurers. Our one.drop technology provides early detection of water leaks through AI-powered IoT sensors, significantly reducing the risk of costly water damage claims. By integrating seamlessly with building systems, one.drop allows insurers to offer proactive protection to their clients, lowering loss ratios and enhancing policyholder satisfaction. With a growing emphasis on ESG and risk mitigation, Enzo’s solution not only helps prevent damage but also supports sustainability goals, positioning insurers as leaders in innovation and customer care.

Enzo is a B2B PropTech and WaterTech startup offering innovative solutions tailored to the needs of insurers. Our one.drop technology provides early detection of water leaks through AI-powered IoT sensors, significantly reducing the risk of costly water damage claims. By integrating seamlessly with building systems, one.drop allows insurers to offer proactive protection to their clients, lowering loss ratios and enhancing policyholder satisfaction. With a growing emphasis on ESG and risk mitigation, Enzo’s solution not only helps prevent damage but also supports sustainability goals, positioning insurers as leaders in innovation and customer care.
What: Enzo develops AI-powered IoT water-leak detection (product: one.drop) to prevent water damage and optimize water use.
HQ: Heidelberg, Germany
Stage: Seed
Team size (approx.): 35 employees
Preventing water damage and reducing water loss in buildings through IoT and AI-driven leak detection and monitoring.
2021
Insurance
Crunchbase lists a Seed round on Jul 12, 2024 and multiple investors including EquityPitcher Ventures and Start-up BW Innovation Fonds.
“Enzo has multiple backers including institutional funds (EquityPitcher Ventures, Start-up BW Innovation Fonds) and individual investors (Gerhard Frieg, Alexander Grimm).”
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Transform the future of insurance through purpose-driven technology
Enzo is a B2B PropTech & WaterTech startup redefining how the property insurance and real estate industries prevent water damage. With our proprietary IoT & AI solution, one.drop , we enable insurers to protect properties before damage occurs, turning reactive claims management into proactive risk mitigation.
At Enzo, AI models only matter if they run reliably, efficiently, and at scale. As our MLOps Engineer, you’ll own the bridge between model development and real-world production, ensuring our AI systems can process millions of sensor data points per day with high performance, reliability, and observability.
You’ll work closely with AI engineers, backend engineers, and the founding team to professionalize our ML infrastructure and deployment pipelines. This is a hands-on, high-impact role with real ownership from day one.
Tasks
Role Overview
As MLOps Engineer, you are responsible for turning ML prototypes into production-grade systems. Your mission is to design, build, and operate a robust ML platform, from data ingestion to inference, monitoring, and CI/CD, that scales with Enzo’s growth and supports fast iteration.
Level: Senior or Mid (5+ Years experience)
Stack: Python, TypeScript, GCP
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What You’ll Do**
ML Infrastructure & CI/CD
Design and implement CI/CD pipelines for ML training and inference.
Build reproducible, versioned model deployment workflows.
Improve environment parity across dev, staging, and production.
Scalable Inference & Performance
Design efficient inference pipelines for time-series models processing millions of sensor data points per day.
Optimize latency, throughput, and cost across cloud infrastructure.
Implement rollout, rollback, and monitoring strategies for ML services.
Data Pipelines & Systems Integration
Build and maintain data pipelines in TypeScript for ingesting, validating, and transforming IoT sensor data.
Collaborate closely with AI engineers working in Python, understand model code and algorithmic requirements.
Ensure clean interfaces between data, models, and applications.
Observability & Reliability
Implement monitoring for model performance, data quality, drift, and system health.
Define failure modes and recovery strategies for ML systems in production.
Improve reliability through automation, testing, and clear operational standards.
Cross-Functional Collaboration
Work side-by-side with AI engineers to make models production-ready.
Challenge assumptions around scalability, cost, and operational risk.
Help establish best practices for ML engineering across the team.
Requirements
Strong Systems Builder
Experience shipping systems into production.
Understanding of ML lifecycles, inference constraints.
Engineering Excellence
Strong understanding of Python ML codebases and algorithms.
Programming skills in TypeScript are a bonus.
Experience with cloud infrastructure (AWS, GCP, or similar).
Performance & Scalability Mindset
You think in terms of throughput, latency, cost, and reliability.
You’ve optimized systems handling large-scale, high-frequency data.
Startup Attitude
Hands-on, pragmatic, and execution-focused.
Comfortable owning systems end-to-end.
You move fast, but you care about doing things right.
Languages
Benefits
Build the foundation for AI systems that prevent real-world damage.
Mission-driven innovation: Help insurers move from paying for damage to preventing it
Direct impact: Your work shapes how an entire industry tackles one of its biggest cost drivers
Autonomy & ownership: Freedom to design, test, and evolve our AI models
Culture of builders: Work alongside a team that values integrity, curiosity, and execution
Flat hierarchies, honest and direct communication with an open-minded startup culture
Free brainfood: unlimited coffee, snacks, drinks, fresh fruits and more
Great career and personal development opportunities - we want you to grow with us
If you’re ready to redefine what partnership means in the insurance industry - and help insurers succeed with Enzo as their trusted innovation partner - we’d love to hear from you.