ML Engineer
Summary
Build and maintain ML infrastructure including data pipelines, ETL workflows, and model deployment using Python, Docker, Kubernetes, GCP/Azure, and orchestration tools like Airflow or Kubeflow.
🔹For our Client we are looking for ML Engineer 🔹
With a focus on IT/OT, R&D, Engineering and Business Development, we deliver sustainable value through a holistic and independent approach to total talent management.
By providing comprehensive talent solutions, combined with vast industry experience and excellence in execution, we form successful collaborations. We bridge clients and partners & professionals throughout the talent supply chain, for the benefit of individuals, organizations and society.
We offer:
Location: Warsaw, 2 days a week from the office
With a focus on IT/OT, R&D, Engineering and Business Development, we deliver sustainable value through a holistic and independent approach to total talent management.
By providing comprehensive talent solutions, combined with vast industry experience and excellence in execution, we form successful collaborations. We bridge clients and partners & professionals throughout the talent supply chain, for the benefit of individuals, organizations and society.
We offer:
- B2B agreement
- Transparent working conditions with both Ework and the client
- Current support during our cooperation
- Possibility to work in an international environment
- Collaborative environment in Swedish organizational culture
Qualifications and Requirements
- A bachelor's or master’s degree in Computer Science, Operations Research, Mathematics and Computing with 3-4 years of relevant experience
- Experience of working with large data sets, coming from varied sources
- Excellent Programming Skills (Python Preferred)
- Experience with containerization (Docker) and container orchestration using Kubernetes
- Experience in Cloud Application Development (Google Cloud Platform & Azure Preferred)
- Great at solving problems; debugging; troubleshooting; and designing & implementing solutions to 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, Git-based workflows
- Comfortable working in Unix/Linux environments
- Hands on experience of designing, building, and supporting RESTful APIs
- Working knowledge of machine learning and deep learning concepts, and experience supporting model deployment and monitoring
Good to have
- Understanding of Deep learning platforms such as Keras, Tensor-flow and/or PyTorch is highly desirable
- In-Depth Understanding of key Machine Learning & Deep Learning Algorithms
- Knowledge of Oilfield terminology and business practices
- Experience with IoT/ Edge technology is a plus
- Recognized open-source contributions
- Familiarity with data engineering tools (Flink/Spark/Kafka etc.)
- Experience with big data stack (Spark, Hadoop, Storm, Hive & Pig) and NoSQL stores is a plus
Behavioural Skills
- Creativity and ability to formulate problems and solve them independently
- Highly collaborative work style
- Strong listening and communications skills
- Presenting & communicating information
- Result and quality focused