100% on-site work required no remote/hybrid options.
We are looking for a skilled and motivated MLOps Engineer to join our software division. This role offers the opportunity to work at the forefront of AI and Big Data technologies, supporting cutting-edge Machine Learning systems in a dynamic, mission-critical environment.
Requirements:
Relevant academic degree in Computer Science, engineering, or a related field mandatory.
Minimum 2 years of experience in MLOps, Machine Learning, or a closely related field mandatory.
Proficiency in Python and ML libraries such as TensorFlow, PyTorch, scikit-learn mandatory.
In-depth knowledge of DevOps tools: Docker, Podman, Kubernetes, Jenkins, Terraform, Ansible mandatory.
Hands-on experience with CI/CD tools (e.g., GitHub, GitLab, Azure DevOps ) and Git mandatory.
Understanding of model deployment, monitoring, and performance optimization mandatory.
Familiarity with data Storage systems: SQL, NoSQL, data Lakehouse mandatory.
Experience with cloud platforms (GCP, AWS, Azure) and managing cloud resources for ML advantage.
Experience with MLOps platforms: ClearML, Kubeflow, MLflow advantage.
Relevant academic degree in Computer Science, engineering, or a related field mandatory.
Minimum 2 years of experience in MLOps, Machine Learning, or a closely related field mandatory.
Proficiency in Python and ML libraries such as TensorFlow, PyTorch, scikit-learn mandatory.
In-depth knowledge of DevOps tools: Docker, Podman, Kubernetes, Jenkins, Terraform, Ansible mandatory.
Hands-on experience with CI/CD tools (e.g., GitHub, GitLab, Azure DevOps ) and Git mandatory.
Understanding of model deployment, monitoring, and performance optimization mandatory.
Familiarity with data Storage systems: SQL, NoSQL, data Lakehouse mandatory.
Experience with cloud platforms (GCP, AWS, Azure) and managing cloud resources for ML advantage.
Experience with MLOps platforms: ClearML, Kubeflow, MLflow advantage.
This position is open to all candidates.
