Member of Technical Staff

Earthian AI; United States; Remote; USD 89,000 - 155,000; Full time

Job summary

Earthian AI seeks a role to build data and software systems supporting risk-focused AI models, from data pipelines to production APIs. The role blends data engineering, applied machine learning, and platform delivery across climate, natural catastrophe, geopolitical, technology, and cyber risk domains.

Locations include Amsterdam, Paris, and Munich, with remote work available within the EU.

Qualifications

• Strong software engineering fundamentals and experience delivering production systems.
• Practical experience in machine learning, data engineering, or applied research.
• Comfort working with Python, cloud infrastructure, and modern ML tools.
• Clear written communication and an ownership-oriented approach.

Responsibilities

• Build and ship pipelines for geospatial, financial, and regulatory data.
• Train, evaluate, and deploy small language models for risk use cases, using rigorous benchmarks.
• Develop reliable APIs and workflows for institutional users.
• Work with research and go-to-market teams on product requirements and customer deployments.
• Improve observability, testing, and model governance across the software stack.

Skills

Strong software engineering

Production systems

Clear written communication

Tools

Python

Cloud infrastructure

ML tools

APIs

Job description

Role overview

Build the data and software systems that support risk-focused AI models, from data pipelines and evaluation tools to production APIs. The role combines data engineering, applied machine learning, and platform delivery across climate, natural catastrophe, geopolitical, technology, and cyber risk domains. It is listed in Amsterdam, Paris, Munich, or remote within the EU.

Responsibilities

• Build and ship pipelines for geospatial, financial, and regulatory data.
• Train, evaluate, and deploy small language models for risk use cases, using rigorous benchmarks.
• Develop reliable APIs and workflows for institutional users.
• Work with research and go-to-market teams on product requirements and customer deployments.
• Improve observability, testing, and model governance across the software stack.

Requirements

• Strong software engineering fundamentals and experience delivering production systems.
• Practical experience in machine learning, data engineering, or applied research.
• Comfort working with Python, cloud infrastructure, and modern machine learning tools.
• Clear written communication and an ownership-oriented approach.

Nice to have

• Interest or previous experience in financial risk, insurance, or capital markets.

Benefits and work setup

• Locations include Amsterdam, Paris, and Munich, with remote work available within the EU.