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Software Engineering
Runpod
Runpod is a cloud platform built for AI workloads, giving developers and companies on-demand access to GPUs for training, fine-tuning and serving models. The company is hiring a Forward Deployed Engineer for the APAC region, a hybrid technical and customer-facing role that sits between revenue and engineering. The position is fully remote and the employer states the requirement plainly as Located in the APAC region (Ideally in Malaysia, Singapore or South Korea), so it is open across multiple countries rather than tied to one office. You would join sales conversations with prospective customers, help new accounts onboard onto the platform, dig into complex technical problems, build proof-of-concept solutions for high-value prospects, and feed what you learn back to product and engineering. Base pay is listed at 100,000 to 160,000 USD per year, converted to local currency, plus stock options, flexible paid time off and a 1,200 USD equipment stipend. Freshness evidence: Runpod Ashby job board publishedAt 2026-09-23.
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Participate in technical sales discussions with prospective customers across APAC and act as the technical point of contact during evaluations. Guide customer onboarding onto the Runpod cloud platform and help teams get their AI inference, fine-tuning and training workloads running. Troubleshoot complex technical issues, reproduce problems and coordinate fixes with engineering. Build proof-of-concept solutions and demos for high-value prospects. Document best practices, integration patterns and reusable solutions, and relay customer feedback to product and engineering teams.
Located in the APAC region, ideally in Malaysia, Singapore or South Korea. Computer science degree or equivalent practical experience. 3 or more years of software development experience. Familiarity with AI and machine learning use cases such as inference, fine-tuning and LLM applications. Strong written and verbal communication skills and comfort working directly with customers. Proficiency in languages and tools such as Python, JavaScript, Go, Docker and machine learning deployment workflows is a plus.
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