Ml Engineer

il y a 7 heures


Eu, France Toogeza Temps plein

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.

**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.

**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**:

- Recruiting Interview — (45 mins)
- Tech + Live Coding (60 mins)
- ML Design + Behavioral (60 mins)
- Cultural Fit interview — (60 mins)


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