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

**
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

• Fluent in English

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.