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Tenstorrent is seeking a Field Application Engineer to drive adoption of its cutting-edge AI platform among enterprise customers. You will serve as a technical bridge between the sales team and customers, leveraging deep expertise in AI/ML to solve real-world problems and shape product direction based on field insights.
In this customer-facing role, you will work directly with enterprise clients in meetings, presentations, and technical workshops to understand their challenges and deliver effective solutions. You'll partner closely with sales operations and product teams to provide customer feedback and influence future product enhancements. Your responsibilities include translating complex technical concepts for both technical researchers and non-technical executives, demonstrating how Tenstorrent's AI platform and custom silicon solve critical performance, cost, and usability challenges.
You'll gain deep exposure to cutting-edge AI technologies—from fine-tuning large language models and optimizing vision models to building scalable AI pipelines on purpose-built hardware. You'll work alongside teams developing hardware, software, compilers, and networking infrastructure, learning how to push the boundaries of AI performance on custom silicon and help developers do the same.
Tenstorrent is building a high-performance RISC-V CPU and unified AI platform that combines innovations in software models, compilers, platforms, networking, and semiconductors. The company values collaboration, curiosity, and a commitment to solving hard problems.
REQUIREMENTS:
- 5+ years of relevant technical, enterprise experience in roles such as Sales Engineer, Solutions Engineer, or Technical Account Manager
- Proven expertise in AI technologies and frameworks: machine learning, deep learning, natural language processing (NLP), computer vision, PyTorch, or TensorFlow
- Experience with embedded systems, FPGA architecture, or AI accelerators
- Strong understanding of data center and server architecture, deployment, thermal/power management, and infrastructure
- Excellent customer-facing and communication skills; ability to convey complex technical concepts to diverse audiences
- Background in AI/ML trenches (field engineering, solutions architecture, or hands-on problem-solving in production environments)
