ML Engineering Professional

6 days ago

Shimoga, Karnataka, India beBeeMachineLearningOperations Full time ₹ 15,00,000 - ₹ 20,00,000

Pursue a career in machine learning operations and engineering.

Key responsibilities include deploying, monitoring, and scaling machine learning models on cloud platforms such as Amazon Web Services (AWS) or Google Cloud Platform (GCP).

You will build and maintain continuous integration and deployment pipelines for machine learning workflows using GitHub Actions or Jenkins.

Containerization and orchestration of workloads with Docker and Kubernetes, as well as infrastructure management via Terraform or CloudFormation, are also crucial aspects of this role.

Implementing model registries, feature stores, and observability using MLflow or Prometheus/Grafana is another key responsibility.

Collaborate with data scientists to operationalize machine learning models for personalization, recommendations, and natural language processing applications.

Proficiency in programming languages such as Python, as well as machine learning frameworks like Scikit-learn, TensorFlow, and PyTorch, and data pipeline tools like Airflow, Spark, and SQL, are essential skills.

Bonus qualifications include experience with real-time machine learning serving, A/B testing, or media/recommender systems.

Nice-to-have qualifications include knowledge of experiment design and causal inference, as well as exposure to real-time machine learning serving technologies like KFServing or Seldon.

In terms of education, a bachelor's or master's degree in a relevant field such as computer science or engineering is typically required.

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