Machine Learning Engineer

We are toogeza, a Ukrainian recruiting company that is focused on hiring talents and building teams for tech startups worldwide. People make a difference in the big game, we may help to find the right ones.

Currently, we are looking for a ML Engineer for The Playa

Location: Remote

Job Type: Full-Time

About our client:

The Playa helps iGaming platforms boost engagement, revenue, and ROMI by up to 25% by understanding and profiling player behavior, detecting positive and suspicious activities, and delivering tailored recommendations to each player.

More information about The Playa solutions can be found on www.theplaya.solutions

Role Overview:

We are looking for an experienced Machine Learning Engineer to build, deploy, and maintain machine learning solutions that are ready for production. In this role, you will solve challenging problems, develop recommendation systems, and improve machine learning workflows to deliver real-world impact.

Responsibilities:

• Design, create, and deploy machine learning models for regression, classification, and clustering.
• Develop and improve recommendation systems to meet business needs.
• Write clean, efficient, and scalable code in Python.
• Use AWS tools and services to build reliable, cloud-based machine learning solutions.
• Manage workflows with Airflow and handle containerized environments using Docker.
• Write and optimize SQL queries for data extraction, transformation, and analysis.
• Work with the team to follow best practices in version control (Git) and testing.
• Apply basic MLOps practices to improve machine learning processes.

Requirements:

Must-Have Skills:

• At least 3 years of hands-on experience in machine learning and data science.
• Strong skills in Python, SQL, and Git.
• Hands-on experience with cloud platforms (preferably AWS), workflow orchestration using Airflow, and containerization with Docker.
• Good understanding of machine learning techniques, such as regression, classification, and clustering.
• Proven ability to deliver robust, scalable, and production-grade code.
• English proficiency at an upper-intermediate level or higher.

Nice-to-Have Skills:

• Experience in building and deploying recommendation systems.
• Familiarity with testing and MLOps practices.
• A Master’s degree in Computer Science, or a related field.

Benefits:

• Education budget of $600 per year provided
• Professional English courses
• Medical Insurance

Interview process:

1. Recruiting Interview — (45 mins)
2. Tech + Live Coding (60 mins)
3. ML Design + Behavioral (60 mins)
4. Cultural Fit interview — (60 mins)

Thanks for your interest! In the case of your application, we will review it within 5 working days. If it meets the job requirements, we will arrange a call and will be happy to get to know each other better. Otherwise, we’d love to stay in touch waiting for other opportunities to become available.