Senior Data/ML Engineer

Responsibilities:

• Managed the lifecycle of machine learning models from development to deployment and monitoring, ensuring optimal performance and reliability
• Implemented MLOps principles, including continuous integration, continuous delivery, testing, and monitoring, to streamline machine learning operations
• Working with Spark & Python to define and maintain data ingestions and transformation, handling both real-time and batch data processing
• Building distributed and highly parallelized big data processing pipeline which process massive amount of data (both structured and unstructured data) in near real-time
• Leverage Spark to enrich and transform corporate data to enable searching, data visualization, and advanced analytics
• Collaborated with cross-functional teams, including data scientists, DevOps engineers, and IT, to deliver high-quality machine learning solutions
• Working closely with analysts and business stakeholders to develop analytics models
• Help in optimizing our current MLOps practices and libraries, make applicable for wider range of use cases outside propensity models
• Cloud solution exploration for AI/ML areas

Requirements:

• Proficiency in programming languages like Python & Spark - minimum 5 years
• Hands-on experience with AWS services for machine learning and data processing - particulary S3, Glue, SageMaker, Lambda and StepFunctions/Airflow/MWAA - covering data ingestion, model training, batch inference and automation pipelines
• Practical understanding of AWS Infrastracture setup and automation using AWS CLI, boto3 and IAM roles, ensuring reproducible and secure ML workflows
• Understanding of algorithms and data structures, knowledge of statistics and linear algebra
• Experience with machine learning frameworks (TensorFlow or PyTorch), including training new ML models, refining existing ones, and deploying these models into user-friendly applications
• Solid understanding of distributed systems with experience in Hadoop/Hive ecosystem and/or other Big Data Technologies
• Proficient in SQL (Spark/Hive SQL), previous experience in creating data flows
• Experience with BitBucket and GIT, code versioning and branching strategy
• Familiar with Agile/SAFe framework
• Very good command of English, both spoken and written

Nice to have:

• Experience in designing and implementing Machine Learning models (e.g., Propensity Models, Customer Lifetime Value, Micro-segmentation, and Channel Recommendation Models)
• Ability to support use case teams in model training and deployment

Offer:

• Private medical care
• Co-financing for the sports card
• Constant support of dedicated consultant
• Employee referral program