Machine Learning Engineer (Infrastructure)
Skills
JavaGoogle Cloud PlatformMachine LearningMachine ToolsPythonTensorflowGoogle Cloud Platform
What the job involves
The main requirements, responsibilities and hiring steps.
Requirements
- Extensive experience as a Machine Learning Engineer or in infrastructure roles focusing on machine learning systems.
- Strong proficiency in Python and Java required.
- Familiarity with machine learning frameworks such as TensorFlow and PyTorch.
- Deep understanding of cloud platforms especially GCP and containerization technologies like Docker and Kubernetes.
- Strong problem-solving and excellent communication skills.
- Experience with big data technologies like Apache Spark or Hadoop is preferred.
Nice to have
- GCP proficiency
- Docker expertise
- Kubernetes experience
- Apache Spark knowledge
Day to day
- Design and build scalable machine learning infrastructure.
- Develop and maintain robust data pipelines using Python or Java.
- Implement and manage cloud-based solutions over platforms like AWS GCP or Azure.
- Collaborate with cross-functional teams to integrate machine learning models into production systems.
- Ensure system reliability and efficiency through proper infrastructure setup and maintenance.