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Staff Software Engineer, Applied AI Engineering
Google
Sunnyvale, USA
Senior · 8+ years experience
USD 207000-300000 / year
Discovered 2 weeks ago
gcp
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Responsibilities
- Architect secure, highly cost-effective distributed systems and MLOps pipelines on Google Cloud Platform (GCP) for fine-tuning and serving frontier models.
- Translate AI/ML research into production-grade services, optimizing model inference latency, throughput, and large-scale TPU/GPU fleet utilization.
- Design robust, self-improving multi-agent architectures and cognitive planning engines capable of executing complex, guardrailed workflows.
- Shape Google Cloud’s AI roadmap by feeding operational insights and technical gaps from incubation projects directly back to core engineering.
- Mentor executive engineers across teams, driving a culture of rapid prototyping, rigorous system design, and technical excellence.
- - Architect secure, highly cost-effective distributed systems and MLOps pipelines on Google Cloud Platform (GCP) for fine-tuning and serving frontier models. - Translate AI/ML research into production-grade services, optimizing model inference latency, throughput, and large-scale TPU/GPU fleet utilization. - Design robust, self-improving multi-agent architectures and cognitive planning engines capable of executing complex, guardrailed workflows. - Shape Google Cloud’s AI roadmap by feeding operational insights and technical gaps from incubation projects directly back to core engineering. - Mentor executive engineers across teams, driving a culture of rapid prototyping, rigorous system design, and technical excellence.
Minimum qualifications:
Bachelor's degree or equivalent practical experience.
8 years of experience in software development.
5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.
5 years of experience leading ML design and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
2 years of experience with GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (language modeling, computer vision).
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