<div class="show-more-less-html__markup show-more-less-html__markup--clamp-after-5 relative overflow-hidden"> <p><strong>Transform the future of insurance through purpose-driven technology</strong></p><br/><p>Enzo is a B2B PropTech &amp; WaterTech startup redefining how the property insurance and real estate industries prevent water damage. With our proprietary IoT &amp; AI solution, <em>one.drop</em>, we enable insurers to protect properties before damage occurs, turning reactive claims management into proactive risk mitigation.</p><br/><p>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.</p><br/><p>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.</p><br/>Tasks<br/><p><strong>Role Overview</strong></p><br/><p>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.</p><br/><p><strong>Level:</strong> Senior or Mid (5+ Years experience)<br/><br/><strong>Stack:</strong> Python, TypeScript, GCP</p><br/><p>**<br/><br/>What You’ll Do**</p><br/><p>ML Infrastructure &amp; CI/CD</p><br/><ul><br/><li>Design and implement CI/CD pipelines for ML training and inference.</li><br/><li>Build reproducible, versioned model deployment workflows.</li><br/><li>Improve environment parity across dev, staging, and production.</li><br/></ul><br/><p>Scalable Inference &amp; Performance</p><br/><ul><br/><li>Design efficient inference pipelines for time-series models processing millions of sensor data points per day.</li><br/><li>Optimize latency, throughput, and cost across cloud infrastructure.</li><br/><li>Implement rollout, rollback, and monitoring strategies for ML services.</li><br/></ul><br/><p>Data Pipelines &amp; Systems Integration</p><br/><ul><br/><li>Build and maintain data pipelines in TypeScript for ingesting, validating, and transforming IoT sensor data.</li><br/><li>Collaborate closely with AI engineers working in Python, understand model code and algorithmic requirements.</li><br/><li>Ensure clean interfaces between data, models, and applications.</li><br/></ul><br/><p>Observability &amp; Reliability</p><br/><ul><br/><li>Implement monitoring for model performance, data quality, drift, and system health.</li><br/><li>Define failure modes and recovery strategies for ML systems in production.</li><br/><li>Improve reliability through automation, testing, and clear operational standards.</li><br/></ul><br/><p>Cross-Functional Collaboration</p><br/><ul><br/><li>Work side-by-side with AI engineers to make models production-ready.</li><br/><li>Challenge assumptions around scalability, cost, and operational risk.</li><br/><li>Help establish best practices for ML engineering across the team.</li><br/></ul><br/>Requirements<br/><p>Strong Systems Builder</p><br/><ul><br/><li>Experience shipping systems into production.</li><br/><li>Understanding of ML lifecycles, inference constraints.</li><br/></ul><br/><p>Engineering Excellence</p><br/><ul><br/><li>Strong understanding of Python ML codebases and algorithms.</li><br/><li>Programming skills in TypeScript are a bonus.</li><br/><li>Experience with cloud infrastructure (AWS, GCP, or similar).</li><br/></ul><br/><p>Performance &amp; Scalability Mindset</p><br/><ul><br/><li>You think in terms of throughput, latency, cost, and reliability.</li><br/><li>You’ve optimized systems handling large-scale, high-frequency data.</li><br/></ul><br/><p>Startup Attitude</p><br/><ul><br/><li>Hands-on, pragmatic, and execution-focused.</li><br/><li>Comfortable owning systems end-to-end.</li><br/><li>You move fast, but you care about doing things right.</li><br/></ul><br/><p>Languages</p><br/><ul><br/><li>Fluent in English</li><br/></ul><br/>Benefits<br/><p><strong>Build the foundation for AI systems that prevent real-world damage.</strong></p><br/><ul><br/><li>Mission-driven innovation: Help insurers move from paying for damage to preventing it</li><br/><li>Direct impact: Your work shapes how an entire industry tackles one of its biggest cost drivers</li><br/><li>Autonomy &amp; ownership: Freedom to design, test, and evolve our AI models</li><br/><li>Culture of builders: Work alongside a team that values integrity, curiosity, and execution</li><br/><li>Flat hierarchies, honest and direct communication with an open-minded startup culture</li><br/><li>Free brainfood: unlimited coffee, snacks, drinks, fresh fruits and more</li><br/><li>Great career and personal development opportunities - we want you to grow with us</li><br/></ul><br/><p>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.</p> </div>