Applied ML Engineer

About the role

Zywa is building an AI operating system for property claims. As an Applied ML Engineer you will turn the massive amount of structured claim data into a usable data asset and ship the first machine‑learning models that drive claim estimations and outcomes.

Key responsibilities

• Design and implement a claims data platform from scratch, covering ingestion, schema design, feature pipelines, storage and orchestration.
• Develop and productionize the first estimation models, starting with gradient‑boosted tabular systems that predict line‑item approval outcomes.
• Define labeling and evaluation strategies for negotiated outcome data.
• Integrate model outputs into live claim workflows and support field agents during go‑lives.
• Build tooling to scale a small ML effort into a robust pipeline, including training pipelines, experiment tracking, serving and monitoring.
• Extend the platform to new use cases such as scope prediction from photos, leakage detection and pricing intelligence.

Required profile

• Hands‑on experience building end‑to‑end data pipelines and production ML systems.
• Comfort working with messy, evolving data schemas and multiple data formats.
• Ability to own the full ML lifecycle without hand‑offs to separate research or data teams.
• Strong collaboration skills to work directly with the CTO and founders.

Required skills

• Gradient‑boosted tabular modeling
• Data ingestion and pipeline development
• Schema design and feature engineering
• Model serving, monitoring and experiment tracking