ML Engineer

Ework Group, founded in 2000 and listed on Nasdaq Stockholm, has around 13,000 independent professionals on assignment. It provides total talent solutions partnering with clients in private and public sectors, focusing on IT/OT, R&D, Engineering, and Business Development. It emphasizes sustainable talent supply chains and operates with a Swedish organizational culture.

• Bachelor's or master's degree in Computer Science, Operations Research, Mathematics, or Computing with 3-4 years of relevant experience
• Experience working with large datasets from varied sources
• Excellent programming skills, preferably in Python
• Experience with containerization using Docker and orchestration using Kubernetes
• Experience in cloud application development with Google Cloud Platform and Azure
• Problem-solving, debugging, troubleshooting, and designing/implementing solutions for complex technical issues
• Experience designing, building, and maintaining ETL workflows and data pipelines using orchestration tools like Apache Airflow, Kubeflow, or similar
• Proficiency with DevOps practices including CI/CD and Git-based workflows
• Comfortable working in Unix/Linux environments
• Hands-on experience designing, building, and supporting RESTful APIs
• Working knowledge of machine learning and deep learning concepts with experience supporting model deployment and monitoring

Nice to have:

• Understanding of deep learning platforms such as Keras, TensorFlow, and/or PyTorch
• In-depth understanding of key Machine Learning and Deep Learning algorithms
• Knowledge of Oilfield terminology and business practices
• Experience with IoT/Edge technology
• Recognized open-source contributions
• Familiarity with data engineering tools like Flink, Spark, and Kafka
• Experience with big data stacks (Spark, Hadoop, Storm, Hive, and Pig) and NoSQL stores

• Script production-ready code
• Leverage GPU and CPU resources appropriately for ML workloads
• Architect, automate, and orchestrate DevOps/ MLOps pipelines on the cloud
• Craft reusable tools and frameworks to monitor, optimize, and maintain ML solutions
• Design and implement data engineering pipelines (ETL)
• Understand business problems and collaborate with the team for scalability and business continuity
• Conduct internal workshops and external meetups, participate in conferences, and give talks
• Continuously evolve skills by keeping up to date with AI/ML developments and upskilling

Location: Warsaw, 2 days per week from the office (hybrid work mode)