Machine Learning Engineer (AI)

TL;DR

Machine Learning Engineer (AI): Designing and developing production data science applications and new AI services from scratch with an accent on maintaining and enhancing data science pipelines in complex high-load applications. Focus on researching and adapting machine learning algorithms for dedicated business needs and performing predictive and statistical modeling.

Location: Capable of working collaboratively in a remote environment

Company

hirify.global is a gaming industry leader founded in 1999, listed on the London Stock Exchange, focused on delivering innovative products and services in regulated and regulating markets.

What you will do

• Develop production data science applications end-to-end using Python.
• Design and develop new AI services from scratch.
• Maintain and enhance existing data science pipelines in complex high-load applications.
• Collaborate closely with R&D and DevOps teams.
• Research, invent, and adapt machine learning algorithms for dedicated business needs.
• Perform predictive and statistical modeling.

Requirements

• Minimum 3 years of experience as a Python developer (including familiarity with PyCharm, git, and debugging).
• Minimum 3 years of experience in predictive modeling, preferably within data science production services.
• At least 3 years of experience in tabular or time series data analysis in a data developer, data scientist, or data analyst role.
• Demonstrate proficiency in SQL for data manipulation and visualization.
• Be a strong team player, with excellent communication skills.
• Have a high level of English proficiency.
• Hold a Bachelor's degree in Engineering, Economics, Mathematics, Statistics, or similar.

Nice to have

• Experience in REST API and cloud deployment.
• Knowledge of AWS or GCP.
• Master's degree in Engineering, Economics, Mathematics, Statistics, or similar.
• Experience in direct communication with business.

Culture & Benefits

• Develop personalized recommendations and churn mitigation strategies for engaged user experiences.
• Generate insightful reports to empower informed, data-driven decisions.
• Constantly explore and integrate new cutting-edge technologies.
• Prioritize responsible user experiences through innovative solutions.
• Embrace differences and maintain transparency in processes.
• Contribute to an inclusive team environment that values diverse thoughts and experiences.