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US 2026 Software - Embedded InternTetraMem Inc • San Jose, Arizona, United States
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US 2026 Software - Embedded Intern

TetraMem Inc
  • US
    San Jose, Arizona, United States
  • US
    San Jose, Arizona, United States
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À propos

At TetraMem, we are redefining the future of AI with our groundbreaking innovations in In-Memory Computing. Leveraging world‑record multi‑level RRAM technology, we deliver highly efficient solutions for AI computations, enabling superior performance and energy efficiency across applications ranging from edge devices to data centers. Our talented team of engineers and industry‑leading executives drives this progress, making TetraMem a leader in advanced memory technologies.
If you are passionate about cutting‑edge technology and thrive in a fast‑paced, collaborative environment, TetraMem is the place for you. Join our global team to shape the future of AI computations and sustainable technology solutions while working at the forefront of innovation. Together, we can make a lasting impact.
Are you ready for new challenges and new opportunities?
Join our team!
Current job opportunities are posted here as they become available.
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About the Role We are seeking a driven Embedded Software Intern to join our engineering team and gain hands‑on experience building the computing fabric of AGI. You’ll work alongside experienced engineers on projects that combine low‑level firmware, high‑performance drivers, and edge AI model deployment.
Responsibilities
Assist in the design, development, and optimization of embedded software and drivers for real‑time and AI workloads.
Support integration and performance tuning on FPGA and ASIC platforms.
Assist in implementing and verifying low‑level optimizations to reduce latency, improve power efficiency, and boost performance.
Assist in testing, debugging, and profiling for system reliability and performance.
Qualifications
Currently pursuing a degree in Computer Science, Electrical Engineering, or related field.
Familiar with C/C++, Rust and Python for embedded systems.
Familiar with AI and Machine learning concepts and models.
Exposure to RTOS, device drivers, and low‑level programming.
Experience with debugging, profiling, and performance tuning.
Experience with embedded software for FPGA, ASIC, or MCU‑based platforms is a plus.
Self‑motivated, eager to learn, and comfortable in a fast‑paced environment.
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  • San Jose, Arizona, United States

Compétences linguistiques

  • English
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