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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 demonstrate the value of Tenstorrent's high-performance RISC-V CPU and AI solutions.
In this customer-facing role, you will:
- Work directly with enterprise customers in meetings, presentations, and technical workshops to understand their challenges and provide effective solutions
- Collaborate closely with sales operations and product teams to gather customer feedback and inform product roadmap decisions
- Demonstrate and optimize AI workloads (generative models, LLMs, computer vision, NLP) on Tenstorrent's custom silicon
- Help customers fine-tune models, optimize inference pipelines, and deploy AI at scale
- Translate complex technical concepts for both technical researchers and non-technical executives
- Provide field insights that shape product features and developer experience
You will gain exposure to cutting-edge AI performance optimization, custom silicon architecture, and the full stack from hardware design through software deployment. This is an opportunity to work alongside teams building hardware, compilers, platforms, and networking solutions from the ground up.
REQUIREMENTS:
- 5+ years of customer-facing technical experience in roles such as Sales Engineer, Solutions Engineer, or Technical Account Manager
- Proven expertise in AI technologies and frameworks: machine learning, deep learning, 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 communication skills to convey complex concepts to diverse audiences
- Background in AI/ML trenches (field engineering, solutions architecture, or hands-on problem-solving)
Note: The posting indicates candidates at various experience levels will be assessed during interviews, and offers will align with assessed level.
