ML Ops 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 an ML Ops Engineer for Play A.

Company domain: i Gaming
Location: remote, EU or Ukraine
Job Type: Full-time

Company:
Playa AI is your trusted AI partner, helping i Gaming platforms and operators increase player engagement and revenue. With years of experience and deep knowledge of the i Gaming industry, they offer tailored solutions that cater to your platform’s unique needs and local market specifics.

Their flagship products, the Player Behavior Engine and Lobby Engine, use advanced AI and machine learning models to provide deep insights into player behavior and deliver personalized game recommendations.

Player Behavior Engine helps you develop detailed player behavior segmentation, spot both positive and negative player activities, and implement personalized actions to enhance player experience and boost revenue. Their Lobby Engine uses advanced AI recommendation models to deliver highly personalized game suggestions directly on the main page. This ensures each player discovers the most relevant games.

Role overview:
As the ML Ops Engineer, you will design, implement, and manage the infrastructure required for training and deploying machine learning models. You will automate and support the deployment and orchestration of ML models to production environments, develop and maintain CI/CD pipelines, and ensure the ML infrastructure's security, reliability, and scalability.

What you will do:

• Design, implement, and manage the environment and infrastructure required for machine learning models training and inference.
  
• Support and automate deployment and orchestration of ML models to production environments.
  
• Develop and maintain CI/CD pipelines for ML models and data pipelines. General release management.
  
• Set up logging, monitor and alerting processes of the deployed models and data pipelines.
  
• Ensure the security, reliability, and scalability of our ML infrastructure. Managing load on the servers.
  
• Manage cloud resources efficiently to optimize cost and performance.
  
• Support and automate the platform integration with other (customer’s) platforms.
  
• Collaborate with data scientists and engineers to streamline the model development and deployment process.
  
• Troubleshoot and resolve issues related to ML infrastructure, deployment, and performance.
  
• Stay up-to-date with the latest developments in ML Ops and cloud technologies.
  

What you need:

• 3+ years of experience in ML Ops, Dev Ops, or related roles (SRE/Cloud Engineer/Infrastructure Engineer, etc).
  
• Strong experience with cloud platforms such as AWS, GCP, or Azure (AWS preferred).
  
• Proficiency in Bash for Linux administration on Virtual Machines.
  
• Proficiency in Python for infrastructure and API Development.
  
• Proficiency with CI/CD tools (Git Lab CI, Jenkins)..
  
• Experience with version control systems (Git).
  
• Experience with SQL for data management.
  
• Experience with Air Flow for process orchestration.
  
• Knowledge of resource management and load balancing solutions.
  
• Experience with containerization technologies (Docker).
  
• Experience of infrastructure-as-code tools (Pulumi, Terraform).
  
• Experience with monitoring and logging tools (Prometheus, Grafana, ELK stack, etc.).
  
• Strong problem-solving skills and attention to detail.
  
• Excellent communication and collaboration skills.
  
• English - at least an Upper - Intermediate level.
  
• Bachelor's or Master’s degree in Computer Science, Engineering, or a related field.
  

Would be a plus:

• Experience with ML frameworks and libraries (Pandas, Scikit-learn, Py Torch etc.).
  
• Knowledge of data engineering and ETL processes.
  
• Knowledge of Big Data (HDFS, Hive, Spark, etc) ecosystem
  
• Understanding of data privacy and security principles.
  

Benefits:

• Education budget of $600 per year provided.
  
• Business travel expenses covered.
  
• Professional English courses.
  
• Medical Insurance.
  

Interview process:

• Recruiting Interview - 45 min;
  
• Interview with CTO - 1.5 hour;
  
• Final Interview with CEO - 60 min;