Currently tracking 489 active AI roles, up 170% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $98k–$505k (avg $233k).
| Title | Stage | AI score |
|---|---|---|
| Software Engineering Manager, Cloud ML Compute Services (Mandarin, English) Software Engineering Manager for Google Cloud's ML Compute Services, focusing on optimizing customer AI/ML models on Google Cloud infrastructure. The role involves leading a team, providing technical guidance, partnering with customers on performance, and collaborating with internal teams to enhance AI workload support. | ServePost-train | 8 |
| Senior Software Engineer, Machine Learning, Debug Senior Software Engineer, Machine Learning, Debug role focused on developing and deploying deep learning models for mosquito-born disease eradication. This involves computer vision for analyzing mosquitoes, statistical modeling for population dynamics, and building production-ready code for scalable deployment, with a focus on optimizing vector control strategies. |
| ServeData |
| 7 |
| Senior Customer Engineer, AI Infrastructure, Google Cloud Senior Customer Engineer focused on AI infrastructure, specifically Google Cloud TPUs, for enterprise clients. This role involves designing, deploying, and optimizing AI training and inferencing solutions, advising on ML operations, and supporting sales teams by solving technical challenges related to AI hardware and software stacks. | ServePost-train | 7 |
| Software Engineering Manager, Content Safety, Infra Software Engineering Manager for Content Safety, focusing on AI/ML infrastructure and deployment for protecting users from harmful content. The role involves leading teams, setting technical direction, and ensuring the scalability and reliability of ML systems. | ServePost-train | 7 |
| Software Engineer, Content Safety, Infra Software Engineer role focused on building and scaling content safety platforms using ML infrastructure and responsible AI techniques to protect users from harmful content. The role involves designing, building, and maintaining these platforms, ensuring quality implementations of company-wide standards for Responsible AI, and collaborating with stakeholders. It requires experience in software development, ML infrastructure, and potentially speech/audio or reinforcement learning. | ServeEval Gate | 7 |