Engineer - MLOps
About the role
The MLOps Engineer role at ORYSYS focuses on streamlining the transition of machine learning models from development to production, ensuring that model lifecycles are automated, monitored, and scalable within the company's AI ecosystem. Key responsibilities include deploying and managing production-ready ML models, implementing automated CI/CD pipelines, setting up monitoring and observability systems, collaborating with data scientists, maintaining engineering standards, and supporting AI infrastructure. The position requires hands-on experience in MLOps, ML Engineering, or DevOps, with a preference for candidates with a background or interest in finance. Technical proficiency in Python, MLOps tools, model serving frameworks, cloud platforms, and DevOps infrastructure is essential.
Must have
- Bachelor’s degree in Computer Science, IT, or a related discipline.
- 2+ years in a hands-on MLOps, ML Engineering, or DevOps role.
- Previous roles: MLOps Engineer, Associate ML Engineer, or DevOps Engineer.
- Experience or strong interest in the finance domain is highly desirable.
- MLOps Tools: MLflow, Kubeflow, DVC, or Vertex AI.
- Model Serving: BentoML, TFServing, or TorchServe.
- Programming: Python (Strong proficiency).
- Cloud Platforms: GCP.
- DevOps/Infra: Docker, Kubernetes, Terraform, and GitHub Actions.
- Ability to fit into the Combank organization & IT culture.
- Excellent attention to detail and analytical skills, specifically regarding model lineage and performance monitoring.
Technologies
- BentoML
- CI/CD
- DevOps
- Docker
- GCP
- GitHub
- GitHub Actions
- Kubeflow
- Kubernetes
- Machine Learning
- MLflow
- MLOps
- Observability
- Python
- Terraform
- Vertex AI
Highlights
Applications should be sent to careers@orysys.com. The role requires fitting into the Combank organization and IT culture. ORYSYS Limited is an equal opportunity employer. No explicit mention of remote work, salary, or location.
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