Data Engineer / ML Engineer (m/f/n)

SHIMI Sp. z o.o.

• Commercial experience in data engineering / ML engineering: 3–4 years.
• Bachelor’s or master’s degree in Computer Science, Operations Research, Mathematics, Computing or a related field.
• Experience working with large datasets from varied sources.
• Strong programming skills, preferably in Python.
• Experience with Docker and containerized environments.
• Experience with container orchestration using Kubernetes.
• Experience in cloud application development, preferably with Google Cloud Platform and/or Microsoft Azure.
• Experience designing, building and maintaining ETL workflows and data pipelines.
• Experience with orchestration tools such as Apache Airflow, Kubeflow or similar.
• Practical knowledge of DevOps practices, including CI/CD and Git-based workflows.
• Good understanding of Unix/Linux environments.
• Hands-on experience designing, building and supporting RESTful APIs.
• Working knowledge of machine learning and deep learning concepts.
• Experience supporting model deployment and monitoring.
• Strong problem-solving, debugging and troubleshooting skills.
• Ability to design and implement solutions to complex technical issues.
• Strong communication skills and collaborative work style.
• Result-oriented and quality-focused approach.
• Availability to work from the client’s office in central Warsaw 2 days per week — mandatory requirement.

Nice to have:

• Experience with deep learning platforms such as Keras, TensorFlow and/or PyTorch.
• In-depth understanding of key machine learning and deep learning algorithms.
• Familiarity with data engineering tools such as Flink, Spark and/or Kafka.
• Experience with big data stack: Spark, Hadoop, Storm, Hive, Pig.
• Experience with NoSQL databases.
• Knowledge of oilfield terminology and business practices.
• Experience with IoT / Edge technologies.
• Recognized open-source contributions.
• Experience presenting technical topics at meetups, conferences or internal workshops.

• Write production-ready code for data and ML solutions.
• Leverage GPU and CPU resources appropriately and understand capacity requirements for ML workloads.
• Architect, automate and orchestrate DevOps / MLOps pipelines in cloud environments.
• Build reusable tools and frameworks to monitor, optimize and maintain ML solutions.
• Design and implement data engineering pipelines, including ETL workflows.
• Collaborate with the team to translate business problems into scalable technical solutions.
• Support business continuity, scalability and appropriate turnaround time for delivered solutions.
• Participate in internal workshops, external meetups and technical knowledge-sharing activities.
• Keep up to date with new developments in AI/ML and related technologies.

Availability to work from the client’s office in central Warsaw 2 days per week is a mandatory requirement.