
Senior Model Deployment Specialist
1 day ago
Prior experience in model deployment, machine learning operations (ML Ops), and data science is required. The ideal candidate should have a strong understanding of cloud-based platforms such as AWS and GCP.
Key Responsibilities:
- Deploy, monitor, and scale ML models on cloud-based platforms.
- Build and maintain continuous integration and delivery (CI/CD) pipelines for ML workflows.
- Containerize and orchestrate workloads with Docker and Kubernetes; manage infrastructure using Terraform or CloudFormation.
- Implement model registries, feature stores, and observability using MLflow, Feast, Prometheus, or Grafana.
- Collaborate with data scientists to operationalize ML models for personalization, recommendations, and natural language processing.
- Proficient in Python, ML frameworks (Scikit-learn, TensorFlow, PyTorch), and data pipelines (Airflow, Spark, SQL).
Bonus Qualifications:
- Experience with real-time ML serving, A/B testing, or media/recommender systems.
- Knowledge of experiment design and causal inference.
- Exposure to real-time ML serving (KFServing, Seldon, Ray Serve).
Education and Experience:
- Bachelor's or Master's degree in a relevant field.
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