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Details of the selected job:

A Senior DevOps Engineer (MLOps) designs the data pipelines and engineering infrastructure to support our clients’ enterprise machine learning systems at scale. They also identify and evaluate new technologies to improve the performance, maintainability, and reliability of the final systems. For this role, it is important to communicate with other departments to build requirements and track progress.

Requirements:

• Advanced Academic Degree in Statistics, Operations Research, Computer Science, Mathematics, Machine Learning, or related field.
• Experience in at least 4 of the following deployment of machine learning and statistical models on a cloud:  MLOps within the enterprise CI/CD process for ML models. Experience deploying ML APIs in production environments in GCP using GKE. Experience in using GCP Vertex AI for ML and BigQuery. Knowledge of Terraform and Containers technologies. Experience writing data processing jobs using GCP Dataflow and Dataproc.  Experience setting up ML model monitoring and autoscaling for ML prediction jobs. Understanding of machine learning concepts to scale ML across different services by leveraging Feature Store, Artifacts Registry, and Analytics Hub.
• Knowledge of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and statistical concepts (regression, properties of distributions, statistical tests, etc.)
• Proven ability to apply modeling and analytical skills to real-world problems.
• Solid programming skills in at least 2 of the following languages R, SQL, Python, TensorFlow, PySpark, Java, JavaScript, or C++.

Benefits:

• Birthday off
• Vacations.

Job Functions:

• Communicate with a team of data scientists, data engineers, and architects to document the processes
• Data science model review, run the code refactoring and optimization, containerization, deployment, versioning, and monitoring of its quality
• Data science models testing, validation, and test automation
• Enforce architectural standards across teams and projects
• Work closely with numerous development teams to design & architect business solutions.

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