The Senior ML Engineer will build and optimize MLOps pipelines, deploy and monitor ML models, and collaborate with Data Scientists and Engineering teams to enhance ML workflows.
At TechBiz Global, we are providing recruitment service to our TOP clients from our portfolio. We are currently seeking a Senior ML Engineer to join one of our clients' team. If you're looking for an exciting opportunity to grow in a innovative environment, this could be the perfect fit for you.
Responsibilities:
- Build, maintain, and optimize end-to-end MLOps pipelines for machine learning workflows.
- Deploy, monitor, and scale machine learning models in production environments.
- Implement CI/CD pipelines for ML workflows and model lifecycle management.
- Manage and optimize ML infrastructure using Docker, Kubernetes, and cloud platforms.
- Collaborate closely with Data Scientists and Engineering teams to productionize ML models.
- Ensure reliability, monitoring, and performance of ML systems in production.
- Maintain best practices for model versioning, experiment tracking, and reproducibility.
Job requirements
Must-Have:
- Senior-level experience in Machine Learning / MLOps engineering
- Strong programming skills in Python
- Hands-on experience with ML frameworks such as:
- TensorFlow
- PyTorch
- scikit-learn
- Experience with MLOps platforms/tools such as:
- MLflow
- Kubeflow
- TFX or similar
- Experience implementing CI/CD pipelines using tools such as:
- Jenkins
- GitLab CI
- CircleCI
- Strong experience with containerization and orchestration:
- Docker
- Kubernetes
- Experience deploying and managing ML solutions on cloud platforms (AWS, GCP, or Azure)
Nice to Have:
- Experience with big data technologies such as:
- Apache Spark
- Hadoop
- Kafka
- Experience with data visualization tools:
- Tableau
- Power BI
Top Skills
AWS
Azure
CircleCI
Docker
GCP
Gitlab Ci
Jenkins
Kubeflow
Kubernetes
Mlflow
Python
PyTorch
Scikit-Learn
TensorFlow
Tfx
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