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Description:
Qarik is an IT Solutions company co-founded by Google Cloud Engineering leaders, focusing on the Google Cloud Platform.
The company has grown to 100 employees in less than three years and serves brand-name clients (F1000).
As an MLOps Engineer specializing in VertexAI, you will develop and manage pipelines for training, hyperparameter tuning, and monitoring model drift.
Your role will involve optimizing machine learning operations, reducing costs, and enhancing performance to ensure the reliability and scalability of models.
Responsibilities include designing, implementing, and maintaining VertexAI pipelines, developing CI/CD pipelines, establishing monitoring systems, maintaining documentation, and proposing enhancements to processes.
Requirements:
Proven experience as an MLOps Engineer or in a similar role, focusing on building and optimizing machine learning pipelines and infrastructure.
Strong proficiency in VertexAI, cloud platforms (preferably GCP), 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.
A Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent experience is required.
Benefits:
Qarik offers a competitive employee compensation and an outstanding benefits package.
The position is fully remote, providing work hours and vacation flexibility for a better work/life balance.
You will be part of a team that values respect, shared goals of customer success, and collaboration over competition.
The company utilizes the latest AI technology, encouraging constant learning and innovation among team members.