Machine Learning Operations (MLOps) Architect (GCP) - Remote

Overview

As a seasoned Machine Learning Operations (MLOps) Architect, you will design, build, and optimize machine learning platforms, focusing on developing scalable inference systems and deploying ML platforms in production environments.

In Short

• Architect and optimize ML Platforms for machine learning and deep learning models.
• Collaborate with cross-functional teams to translate business objectives into engineering solutions.
• Lead development and operation of high-performance inference systems.
• Provide technical leadership and mentorship to engineering teams.
• Develop CI/CD workflows for ML models and data pipelines.
• Automate model training, validation, and deployment.
• Monitor and maintain ML models in production.
• Ensure reproducibility of experiments using ML metadata tracking tools.
• Manage model versioning and rollbacks.
• Optimize model inference infrastructure for efficiency.

Requirements

• Bachelor's degree in computer science or related field.
• 5+ years of relevant industry experience.
• Experience in designing scalable machine learning inference systems.
• Hands-on experience with TensorFlow, PyTorch, and Hugging Face.
• Experience with Google Cloud Platform (GCP) services.
• Strong problem-solving skills and critical thinking.
• Effective communication skills for remote work environments.
• Expertise in public cloud platforms, especially GCP.
• Experience in building agentic AI systems.
• In-depth understanding of large language model architectures.

Benefits

• Opportunity to work with cutting-edge technology.
• Professional and personal growth commitment.
• Collaborative work environment.
• Engaging challenges solving complex business problems.
• Supportive team culture.