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Tenstorrent University Jobs

Software Engineering Intern, Power Modeling & AI Tools

Santa Clara, California, United StatesinternshipinternAdded yesterday

About this role

Tenstorrent seeks a Software Engineering Intern to develop power modeling tools and AI-enabled workflows for next-generation CPU and AI products. You'll build automation scripts, data visualizations, and internal tools while gaining exposure to hardware systems, LLMs, and semiconductor engineering challenges.

What you'll do

  • Develop tools and automation scripts to scale power modeling workflows for CPU and AI products
  • Integrate and analyze complex engineering datasets to improve accessibility and actionability
  • Create visualizations and dashboards to communicate technical insights to engineering teams
  • Support workload profiling, model validation, and analytics to enhance power model accuracy
  • Contribute to LLM-based and agentic AI interfaces for engineering productivity
  • Follow modern software development practices including Git-based workflows and code reviews

What they're looking for

  • Python programming
  • SQL and database querying
  • Data visualization and dashboard development
  • Git and version control
  • Jupyter notebooks and code-first analysis
  • Shell scripting and automation
  • Problem-solving with technical datasets
  • LLM and AI tool familiarity

Benefits

  • Competitive hourly compensation ($50–$70/hr)
  • Exposure to cutting-edge AI and semiconductor technology
  • Mentorship from experienced engineers on real-world power modeling challenges
  • Experience with modern AI workflows including LLMs and agents
  • Flexible internship terms (Winter, Summer, Fall) aligned with academic schedules
  • Equal opportunity employer with competitive benefits
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Tenstorrent University Jobs

Tenstorrent builds high-performance AI accelerator chips and compiler technologies for machine learning workloads. The company is hiring interns for roles in AI compilers, chip design verification, and machine learning-based physical design optimization across multiple locations.

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Likely interview questions

  • Walk us through a project where you analyzed a complex dataset and built a tool or visualization to communicate insights—what was your approach?
  • Describe your experience with Python scripting and data analysis environments like Jupyter notebooks.
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