
Cloud-Based Machine Learning Professional
23 hours ago
Prior to this role, you should have ~2+ years of experience working with cloud-based machine learning platforms.
Key Responsibilities:Deploy, monitor and scale machine learning models on cloud platforms such as Amazon Web Services (AWS) or Google Cloud Platform (GCP).
Build 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 or Feast.
Collaborate with data scientists to operationalize machine learning models for personalization, recommendations and natural language processing.
You should be proficient in Python, machine learning frameworks (scikit-learn, TensorFlow, PyTorch) and data pipelines (Apache Airflow, Apache Spark, SQL).
Nice-to-Haves:Experience with subscription-based services, media recommendation systems or recommender systems.
Knowledge of experiment design and causal inference techniques.
Exposure to real-time machine learning serving technologies (KFServing, Seldon, Ray Serve).
A bachelor's or master's degree in a related field is required for this position.
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