Applied ML Engineer – AI & Property Claims | Dubai, UAE

Location

Dubai, United Arab Emirates — On-site

Job Category

• Information Technology (IT) & Software
• Science & Research
• Finance & Accounting
• Insurance & Banking

Job Overview

Zywa is seeking an Applied Machine Learning Engineer to build production-grade machine learning systems for Cozmo, an AI operating system designed for property insurance claims. The role will cover the complete ML lifecycle, from raw data ingestion and data pipelines through model development, deployment, monitoring, and integration into live claims workflows.

The successful candidate will build claims data platforms and pipelines, develop structured and tabular machine learning models, design feature pipelines, and apply ML to areas including claim approval, pricing, leakage detection, and information extracted from photographs and call transcripts. The position involves significant ownership of production ML infrastructure and direct collaboration with the CTO and founders.

This is a high-ownership opportunity for professionals seeking career growth in applied machine learning, AI systems, insurance technology, data engineering, and production ML. The role offers founding-level equity and exposure to an early-stage startup environment where engineers are expected to take end-to-end ownership of ML systems.

Key Responsibilities

• Build the claims data platform and data pipelines from the ground up.
• Develop production data pipelines using Python, SQL, dbt, and Spark.
• Implement data orchestration and scalable data-processing workflows.
• Design database schemas and machine learning feature pipelines.
• Develop gradient-boosting and other tabular machine learning models.
• Build models to predict claim and line-item approval outcomes.
• Develop machine learning solutions for pricing and leakage detection.
• Apply machine learning to property photographs and call transcripts.
• Build model training and experimentation workflows.
• Implement experiment tracking and model-serving infrastructure.
• Develop ML monitoring and production observability systems.
• Deploy machine learning models into live production environments.
• Integrate ML outputs into agent workflows and claims operations.
• Take end-to-end ownership of machine learning systems from data preparation through production.
• Work directly with the CTO and founders on product and ML initiatives.
• Identify data quality, labeling, and data leakage issues.
• Develop scalable solutions for real-world insurance claims data.

Requirements & Qualifications

• 2–6 years of production machine learning experience.
• Strong Python programming skills.
• Strong SQL skills.
• Experience with dbt and/or Spark.
• Experience building production data pipelines.
• Experience deploying machine learning systems and infrastructure.
• Strong understanding of tabular and structured machine learning.
• Experience with gradient-boosting algorithms.
• Experience with data labeling and identifying data leakage.
• Demonstrated ability to own ML projects end-to-end.
• Strong problem-solving and analytical skills.
• Effective written and verbal communication.
• Ability to work in a fast-paced, high-ownership startup environment.

Preferred Experience

• Document, photograph, or transcript extraction.
• Insurance, pricing, risk, or marketplace technology.
• LLM engineering.
• AI agents and tool-use systems.
• Experience building production AI applications.

Salary, Benefits & Career Growth

Compensation

Salary: $100,000–$240,000 per year

The position also includes founding-level equity.

This is a high-ownership role offering professional development across applied machine learning, data engineering, ML infrastructure, AI product development, insurance technology, and production model deployment.

Career growth opportunities include developing expertise in end-to-end ML system ownership, AI architecture, data platforms, model serving, experimentation, and AI-powered insurance products. Working directly with the CTO and founders also provides exposure to product strategy and technical decision-making within an early-stage technology company.

Work Environment

• Primarily in-person.
• Fast-paced startup environment.
• High level of individual ownership.
• Almost six-day working weeks.
• Founding-level equity opportunity.

Application Process

Application Process (Website)

Apply through the official job link and click Apply Now on the website.

Application Requirements

Candidates should submit three items:

1. The best ML or data pipeline they have built, including code or a technical write-up.
2. A video of less than 60 seconds explaining why training directly on negotiated insurance-claim labels can create problems and how they would address the issue.
3. Preferred city and earliest possible joining date.

No cover letter is required.

An exceptional response to the ML question may lead to an interview even without a strong resume.

Official Job Link

Apply through the LinkedIn job listing for Applied ML Engineer at Zywa.