Senior / Principal Machine Learning Engineer

Requirements

• 6+ years of commercial experience in Machine Learning and Big Data engineering
• Strong hands-on experience with machine learning algorithms implementation using Python
• Proven experience with Apache Spark and large-scale distributed data processing
• Experience working with distributed messaging systems such as Kafka
• Strong knowledge of AWS cloud services and cloud-native architectures
• Experience designing and developing large-scale distributed or mission-critical systems
• Solid understanding of software engineering principles, SDLC, and Agile methodologies
• Strong analytical thinking and problem-solving skills
• Ability to work independently and take ownership of complex technical solutions
• Good communication and collaboration skills
• Upper-Intermediate or higher English level

WILL BE A PLUS:

• Experience with Golang
• Experience in AdTech, online advertising, or media platforms
• Experience with forecasting systems or recommendation engines
• Experience optimizing ML models for large-scale production environments

Responsibilities

• Design, develop, and optimize scalable Machine Learning models for advertising intelligence and forecasting systems
• Analyze large-scale historical and real-time datasets to improve forecasting accuracy and monetization strategies
• Build and maintain distributed data processing pipelines using Spark and related Big Data technologies
• Develop production-ready ML solutions using Python within AWS cloud infrastructure
• Research, evaluate, and implement Machine Learning algorithms suitable for high-load AdTech environments
• Improve model performance, scalability, reliability, and operational efficiency
• Collaborate with Data Engineers, Product Managers, and distributed engineering teams to deliver end-to-end ML solutions
• Contribute to ML architecture decisions, experimentation approaches, and engineering best practices
• Monitor, validate, and optimize ML model quality and forecasting performance in production environments
• Produce technical documentation related to ML pipelines, models, and distributed systems
• Mentor engineers and support technical growth within the team
• Drive innovation in Machine Learning and AdTech technologies