Job Opportunity: Practice Specialist, Machine Learning and Infrastructure, Google Cloud

Company: Google

Minimum Qualifications

• Bachelor's degree in Computer Science, Mathematics, a related technical field, or equivalent practical experience.
• 5 years of experience in machine learning algorithms, statistical analysis, data mining, and model evaluation.
• Experience with large language models (LLM), multimodal models, and other generative AI techniques.
• Proficiency in Python, PyTorch, and Jupyter/Colab notebooks.

Preferred Qualifications

• Experience with cloud-based Machine Learning platforms such as Google Cloud Vertex Platform.
• Proven experience in training and fine-tuning large models (image, language, etc.) using accelerators like GPUs and TPUs.
• Experience with performance profiling tools such as TensorFlow Profiler, PyTorch Profiler, and TensorBoard.
• Familiarity with libraries and frameworks like Hugging Face Transformers, CUDA, and XLA (e.g., TPUs).
• Knowledge of Machine Learning performance benchmarks, distributed training, and optimizing performance and cost trade-offs.

About the Job

The Google Cloud Platform team is at the forefront of customer digital transformation. We offer secure, reliable, and scalable products from infrastructure to applications, helping various sectors—including developers, businesses, educational institutions, and government agencies—realize the full potential of cloud technology.

As a Practice Specialist in Machine Learning and Infrastructure at Google Cloud, you will play a pivotal role in understanding customer needs and shaping the future of technology use within businesses. Your responsibilities will involve guiding platform architecture, migration strategies, and cost/performance analysis to train and serve Machine Learning models at scale. You will collaborate with cross-functional AI teams, Product and Engineering, Infrastructure, and Kubernetes specialists to deliver optimal solutions for our customers.

Google Cloud accelerates the digital transformation of organizations worldwide by delivering enterprise-grade solutions with cutting-edge technology. Our tools help developers build more sustainably, with customers in over 200 countries and territories relying on us to solve their critical business challenges.

Responsibilities

• Guide customers on integrating Google Cloud AI accelerators (e.g., GPUs, TPUs) into their overall cloud strategy. Recommend optimal migration paths, integration strategies, and architectures that enhance performance and cost-efficiency.
• Showcase Google Cloud's AI accelerators' capabilities and unique advantages through proof-of-concept projects.
• Collaborate with customers to optimize their machine learning models for performance, scalability, and cost-efficiency on Google Cloud infrastructure.
• Develop and deliver technical content, including best practices, tutorials, code samples, and presentations, to help customers and internal teams effectively use Google Cloud AI infrastructure.
• Represent Google Cloud at customer locations, conferences, meetups, and other industry events to share knowledge, network, and stay up-to-date with the latest trends.

Apply now to join Google Cloud and play a decisive role in shaping the future of business technology.