
Senior Cloud Machine Learning Engineer
5 days ago
Prior to this role, you have worked with ML Ops & DS for over 2 years.
Key Responsibilities:
- Deploy, monitor and scale machine learning models on cloud platforms like AWS or GCP.
- Build and maintain continuous integration/deployment pipelines for machine learning workflows using GitHub Actions/Jenkins/cloud-native tools.
- Containerize and orchestrate workloads with Docker/Kubernetes and manage infrastructure via Terraform/CloudFormation.
- Implement model registries, feature stores and observability using MLflow, Feast, Prometheus/Grafana.
- Collaborate with data scientists to operationalize machine learning models for personalization, recommendations, natural language processing.
Required Skills:
- Proficient in Python and machine learning frameworks such as Scikit-learn, TensorFlow, PyTorch.
- Experience with data pipelines such as Airflow, Spark, SQL.
- Knowledge of experiment design and causal inference.
Bonus Experience:
- Real-time machine learning serving, A/B testing, or media/recommender systems.
Nice-to-Have:
- Experience with subscription, media, or recommender systems.
- Exposure to real-time machine learning serving (KFServing, Seldon, Ray Serve).
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