Field Application Engineer

We’re looking for a Field Application Engineer who’s wired for AI/ML, fluent in real-world problem-solving, and excited to build with the people actually using what we make. You will collaborate closely with the sales team and enterprise customers, leveraging your deep technical knowledge in AI to drive the adoption of our products and solutions. This is a customer-facing role that requires both technical expertise and excellent communication skills to convey complex technical concepts to non-technical stakeholders. This role is hybrid, based out of Tokyo, Japan. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting.

This role is hybrid, based out of Tokyo, Japan.

• You’ve lived in the AI/ML trenches, whether as a field engineer, a solutions architect, or the one tapped in when things needed to “just work.”
• You speak both machine and human. Whether it’s a researcher or a skeptical executive, you know how to break things down and bring them to life.
• You’re fired up about generative models, LLMs, and the edge of what’s possible when software meets purpose-built silicon.
• Engage directly with customers in meetings, presentations, and workshops to understand their technical challenges and provide effective solutions.
• Work closely with sales operations and product teams to provide feedback from customers and help shape future product enhancements.
• Strong customer-facing skills with 5+ years of relevant technical, enterprise experience (such as Sales Engineer, Solutions Engineer, or Technical Account Manager). Must be fluent in Japanese and business level English
• Your field insight will help shape our roadmap, our features, and the way we show up for developers.
• Proven expertise in AI technologies and frameworks, including machine learning, deep learning, natural language processing (NLP),computer vision, PyTorch or TensorFlow.
• Experience with GPU, CUDA or AI accelerators. Familiarity with hardware/software co-optimization is often critical for efficient inference at the edge.
• Good understanding of data center, server architecture and deployment, thermal/power, and infrastructure management
• Explore how to push the boundaries of AI performance on custom silicon and help developers do the same.
• Experience what it’s like to build the future from scratch, working alongside teams creating hardware, software, and everything in between.
• Master the craft of fine-tuning LLMs, optimizing vision models, and building AI pipelines that run at scale.
• Understand why field roles drive real impact turning on-the-ground insight into product breakthroughs and platform momentum.