Remote AI Field Applications Engineer – AI/ML & Embedded

Tenstorrent Unlisted/Referral Jobs

United States

Remote

USD 120,000 - 180,000

Full time

14 days+

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Job summary

Tenstorrent is seeking a Field Application Engineer with AI/ML expertise to drive adoption of our AI platform with enterprise customers. This remote role collaborates with sales and product teams, translating complex technical concepts into practical solutions for researchers and executives alike.

The position is remote based out of Gdansk, Poland, supporting customers globally. We welcome applicants across experience levels; offers align with level demonstrated during the interview, and

Qualifications

  • 5+ years of technical, enterprise experience in roles such as Sales Engineer, Solutions Engineer, or Technical Account Manager.
  • Proven AI/ML knowledge across frameworks and real-world applications.
  • Ability to translate complex technical topics for non-technical stakeholders.

Responsibilities

  • Engage with enterprise customers in meetings, presentations, and workshops to understand challenges and propose solutions (customer-facing).
  • Collaborate with sales operations and product teams to relay customer feedback and guide product enhancements.
  • Explain AI/ML concepts clearly to researchers and executives, bridging between software and hardware.
  • Drive adoption of Tenstorrent AI products by showcasing value and use cases to customers.

Skills

5+ years experience (customer-facing)
AI/ML expertise
Strong communication
Technical problem solving

Tools

PyTorch
TensorFlow
FPGA tools

Job description

Tenstorrent is seeking a Field Application Engineer with AI/ML expertise to drive adoption of our AI platform with enterprise customers. This remote role collaborates with sales and product teams, translating complex technical concepts into practical solutions for researchers and executives alike.

The position is remote based out of Gdansk, Poland, supporting customers globally. We welcome applicants across experience levels; offers align with level demonstrated during the interview, and

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