Senior Data/ML Engineer

2 dni temu

Warszawa, Mazovia, Polska B2Bnetwork Pełny etat
Responsibilities
  • Managing the full lifecycle of machine learning models – from development, through deployment, to monitoring, ensuring optimal performance and reliability
  • Implementing MLOps principles, including continuous integration (CI), continuous delivery (CD), testing, and monitoring to streamline machine learning operations
  • Working with Spark and Python to define and maintain data ingestion and transformation processes, handling both real-time and batch data processing
  • Building distributed and highly parallelized Big Data processing pipelines that handle massive volumes of data (both structured and unstructured) in near real-time
  • Leveraging Apache Spark to enrich and transform corporate data to support search, data visualization, and advanced analytics
  • Collaborating with cross-functional teams, including data scientists, DevOps engineers, and IT teams, to deliver high-quality machine learning solutions
  • Working closely with analysts and business stakeholders to develop analytics models
  • Supporting the optimization of current MLOps practices and libraries and adapting them for a broader range of use cases beyond propensity models
  • Exploring cloud-based solutions in the AI/ML domain
Required Skills and Experience (Must-have)
  • Proficiency in Python and Spark programming - minimum 5 years of experience
  • Hands-on experience with AWS services for machine learning and data processing, particularly S3, Glue, SageMaker, Lambda, and Step Functions/Airflow/ MWAA, covering data ingestion, model training, batch inference, and automation pipelines
  • Practical understanding of AWS infrastructure setup and automation using AWS CLI, boto3, and IAM roles, ensuring reproducible and secure ML workflows
  • Solid understanding of algorithms and data structures, with knowledge of statistics and linear algebra
  • Experience with machine learning frameworks (TensorFlow or PyTorch), including training new ML models, enhancing existing ones, and deploying them into user-facing applications
  • Strong understanding of distributed systems, with experience in the Hadoop/Hive ecosystem and/or other Big Data technologies
  • Proficiency in SQL (Spark SQL/Hive SQL) and prior experience in creating data pipelines
  • Experience working with Bitbucket and GIT, including code versioning and branching strategies
  • Familiarity with Agile/SAFe frameworks
Nice-to-have
  • Design and implementation of ML models such as propensity models, Customer Lifetime Value (CLV), micro-segmentation, and channel recommendation models, as well as supporting use case teams in model training and deployment

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