Remote ML & Simulation Engineer for DeFi Analytics

Cenit Finance (acquired by Space and Time); Madrid; Remote; EUR 65,000 - 90,000; Full time

Benefits offered by this job

Remote first company

Biannual off-site retreats

Amazing office in Madrid’s City Center

Laptop, monitor of your choose

Flexible working hours

Job summary

Machine Learning & Simulation Engineer at Cenit.Finance is seeking someone to develop our core agent-based simulation engine and machine learning models in a remote-friendly Madrid setting. You will contribute to building scalable software and risk analytics for DeFi protocols.

You will work in an agile environment, gather requirements, implement solutions, and improve the Python SDK while delivering actionable insights from simulations to customers.

Qualifications

• Bachelor’s degree in Computer Science or related field, or equivalent knowledge, skills, and industry experience.
• +3 years of engineering experience in the industry.
• Proficient in writing Python code and experience working with the Python data science stack.

Responsibilities

• Help our team in the development of Machine Learning models and agent-based simulations.
• Extract understandable and actionable insights from the data generated in our simulations for our customers.
• Work in a truly agile environment, able to gather and understand requirements, propose solutions, and build them.
• Improve our internal Python SDK.
• Design and build software that is highly available, performant, scalable, and extensible.

Skills

Python

Data science stack

Machine Learning

Agent-based simulations

Education

Bachelor’s degree in Computer Science or related field

Tools

Python SDK

Job description

Machine Learning & Simulation Engineer at Cenit.Finance is seeking someone to develop our core agent-based simulation engine and machine learning models in a remote-friendly Madrid setting. You will contribute to building scalable software and risk analytics for DeFi protocols.

You will work in an agile environment, gather requirements, implement solutions, and improve the Python SDK while delivering actionable insights from simulations to customers.