Senior Machine Learning Engineer (m/f/d) at Kayzen

Kayzen is seeking a Senior Machine Learning Engineer to join their Machine Learning Engineering team. The role involves bridging the gap between data science and ad systems engineering, working with petabyte-scale data models to create innovative solutions. The Senior Machine Learning Engineer will help revolutionize the AdTech space with machine learning.

Responsibilities:

• Accelerate Experimentation and Deployment by creating solutions to streamline model experimentation and deployment processes.
• Maintain and enhance model monitoring capabilities to ensure optimal performance in production.
• Collaborate with data scientists to develop new models and research novel methods.
• Develop and productionalize model creation pipelines for ML models in bare-metal and cloud environments.
• Propose and lead projects to continuously improve machine learning capabilities.
• Promote and implement software engineering best practices to ensure the reliability, maintainability, and scalability of machine learning systems.

Requirements:

• 5+ years of experience deploying big data-based models from conceptualization to deployment.
• Experience with ML tools (AWS Sagemaker, AIM, Catboost, VW, Redash, etc).
• Proven experience with Machine Learning techniques (Neural Networks, Random Forest, etc.) and ML frameworks (Catboost, Mlflow, PyTorch, Tensorflow, etc.).
• Fluency in relevant programming languages (Python, Java, etc.).
• Strong proficiency in SQL & NoSQL and big data processing pipelines (Python, Spark, Airflow).
• Bachelor's/Master's degree in Mathematics, Physics, Computer Science, Machine Learning Engineering, or a related field.
• Strong analytical and problem-solving skills.
• Excellent stakeholder management and communication skills.

Kayzen offers:

• Exceptional career growth and learning opportunity
• A unique opportunity to be part of an experienced team of industry experts and entrepreneurs
• Direct, day-to-day work experience with the management
• A fun, driven, and multinational team
• A flexible work-from-home arrangement
• A 500-dollar home-office setup budget
• A 1000-dollar annual learning and development budget