Senior Machine Learning Engineer

August 8

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Co-create Your Cloud-Native Future with Qarik: Go further, faster.

Google Cloud Migrations • Machine Learning • Kubernetes • Data Analytics • Google Cloud Platform

51 - 200

Description

• Design, implement, and maintain VertexAI pipelines for model training, hyperparameter tuning, and model drift detection. • Develop and optimize CI/CD pipelines for seamless integration and deployment of machine learning models. • Establish monitoring and alerting systems to track model performance, health, and data drift, ensuring timely identification and resolution of issues. • Maintain comprehensive documentation of pipelines, processes, and best practices to ensure reproducibility and knowledge sharing. • Stay updated with the latest advancements in MLOps tools, technologies, and methodologies, and propose enhancements to existing processes.

Requirements

• Proven experience as an MLOps Engineer or similar role, with a focus on building and optimizing machine learning pipelines and infrastructure. • Strong proficiency in VertexAI, cloud platforms (GCP preferred), containerization technologies (Docker, Kubernetes), and orchestration tools (Kubeflow, Airflow). • Proficiency in programming languages such as Python, with experience in ML frameworks like TensorFlow or PyTorch. • Extensive experience with CI/CD tools and practices, including version control systems (Git) and automation tools. • Excellent problem-solving skills and the ability to troubleshoot complex issues in a fast-paced environment. • Strong communication and collaboration skills, with the ability to work effectively in cross-functional teams. • Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent experience.