Senior Machine Learning Operations Specialist

7 days ago


mount, India beBeeMachineLearningEngineer Full time

Machine Learning EngineerPrior experience of two years or more working in machine learning operations and data science is required.Responsibilities include deploying, monitoring, and scaling machine learning models on cloud platforms such as AWS or GCP. This involves using tools like SageMaker, EKS, Lambda, Vertex AI, GKE, and Cloud Functions.Another key responsibility is building and maintaining continuous integration and continuous deployment pipelines for machine learning workflows using GitHub Actions, Jenkins, or cloud-native tools. Containerization and orchestration of workloads are also necessary using Docker and Kubernetes, while infrastructure management is handled via Terraform or CloudFormation.Implementing model registries, feature stores, and observability using MLflow, Feast, Prometheus, and Grafana is an essential task. Collaboration with data scientists to operationalize machine learning models for personalization, recommendations, and NLP is also required.Proficiency in Python, machine learning frameworks (Scikit-learn, TensorFlow, PyTorch), and data pipelines (Airflow, Spark, SQL) is necessary. Bonus points are awarded for experience with real-time machine learning serving, A/B testing, or media/recommender systems. Nice-to-have skills include knowledge of subscription, media, or recommender systems, experiment design, and causal inference. Exposure to real-time machine learning serving (KFServing, Seldon, Ray Serve) is desirable.



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