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

• 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.