
Cloud-Based Machine Learning Engineer
1 day ago
Prior to this role, you have had experience working with Machine Learning Operations and Data Science for over two years.
We are seeking a skilled professional to help us deploy, monitor, and scale our Machine Learning models on cloud-based platforms such as AWS or GCP.
Key Responsibilities:
- Develop and maintain Continuous Integration/Continuous Deployment pipelines for Machine Learning workflows using GitHub Actions or Jenkins.
- Containerize and orchestrate workloads with Docker and Kubernetes; manage infrastructure via Terraform or CloudFormation.
- Implement model registries, feature stores, and observability using MLflow, Feast, Prometheus, or Grafana.
Required Skills and Qualifications:
- Collaborate with data scientists to operationalize Machine Learning models for personalization, recommendations, and NLP.
- Proficient in Python and various Machine Learning frameworks such as Scikit-learn, TensorFlow, and PyTorch.
- Experience with data pipelines including Airflow, Spark, and SQL.
Bonus Qualifications:
- Experience with real-time Machine Learning serving, A/B testing, or media/recommender systems.
Nice-to-Have Qualifications:
- Knowledge of experiment design and causal inference.
- Exposure to real-time Machine Learning serving platforms like KFServing, Seldon, or Ray Serve.
Education:
- Bachelor's or Master's degree in a relevant field.
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