AI Platform Support Engineer (APAC)

Role overview Support machine learning teams running large training and inference workloads in production across cloud infrastructure, Kubernetes, and GPU platforms. This is a hands-on technical role focused on diagnosing complex failures, improving reliability, and helping customers navigate distributed systems, rather than simply routing support requests. The position is part of an APAC customer experience team and is open to candidates in the Philippines or Singapore.

Responsibilities - Investigate production issues involving Kubernetes scheduling, distributed workloads, cloud infrastructure, and GPU systems. - Work directly with ML engineers to identify causes of failures and guide them through solutions. - Help improve reliability and performance for training and inference workloads. - Communicate technical findings clearly and collaborate with engineering teams on recurring issues. - Take ownership of customer problems and contribute to better support practices and platform operations.

Requirements - Strong technical experience supporting cloud, Kubernetes, and GPU-based environments. - Ability to troubleshoot distributed systems and production workloads methodically. - Clear written and verbal communication, with a collaborative approach to customer problems. - Comfort working in a fast-moving, ambiguous environment and taking responsibility for outcomes. - Practical, continuous learning mindset and interest in improving systems over time.

Nice to have - Experience with large-scale model training or distributed inference. - Familiarity with Ray, Kubeflow, Slurm, or similar schedulers; InfiniBand, RDMA, or high-performance networking; bare-metal infrastructure; or storage used in ML systems. - Background in AI infrastructure, cloud, MLOps, developer tooling, or platform engineering. - Experience creating operational tooling or automation with Python or a similar language.

Benefits and work setup Benefits may vary by location and role. Listed offerings include health coverage, equity, paid time off and holidays, parental and family leave, professional development support, wellness and work-from-home stipends, and flexible schedules. A hybrid model is offered for office-based teams.