machine learning infrastructure engineers

At Shopify, we are committed to building robust and scalable machine learning platforms that empower our data scientists and engineers to innovate and deliver exceptional AI solutions. Our team is dedicated to creating an infrastructure that enables seamless model development, deployment, and monitoring. We are looking for skilled Machine Learning Infrastructure Engineers to join our team and help us shape the future of AI.

As a Machine Learning Infrastructure Engineer, you will design, implement, and maintain the underlying infrastructure that supports our machine learning initiatives. You will collaborate closely with Machine Learning Engineers and Data Scientists to ensure that they have the tools and resources necessary to build and deploy high-quality models efficiently. Your expertise in cloud computing, data pipelines, and system architecture will be critical in enabling our team to deliver impactful AI solutions.

Key Responsibilities:

• Design and build scalable machine learning infrastructure, including data pipelines, model training environments, and deployment frameworks.
• Collaborate with Machine Learning Engineers to understand their requirements and provide solutions that enhance their productivity.
• Optimize infrastructure for performance, reliability, and cost-effectiveness, ensuring that it can handle large-scale machine learning workloads.
• Implement monitoring and logging solutions to track model performance and infrastructure health.
• Stay current with emerging technologies and best practices in machine learning infrastructure and cloud computing.
• Document and communicate infrastructure architecture, processes, and best practices to the team.

Qualifications:

• Proven experience in building and maintaining machine learning infrastructure or data engineering pipelines.
• Proficiency in cloud platforms (e.g., AWS, Azure, Google Cloud) and containerization technologies (e.g., Docker, Kubernetes).
• Strong programming skills in Python or Scala, with experience in ML frameworks (e.g., TensorFlow, PyTorch).
• Familiarity with data storage solutions, ETL processes, and distributed computing frameworks (e.g., Apache Spark).
• Excellent problem-solving skills and the ability to work collaboratively in a fast-paced environment.