Machine Learning Applications & Benchmarking Intern

Requirements

• Background in computer science, ML, or a related field.
• Proficient in Python with experience using PyTorch or TensorFlow.
• Comfortable writing clean, reproducible code and debugging performance issues.
• Curious, collaborative, and always looking to learn something new.
• What We Need:
• Benchmark ML models across hardware setups and analyze performance.
• Identify slowdowns and optimize for speed and efficiency.
• Build demos and apps that highlight real ML use cases on our hardware.
• Contribute to software testing and release validation.
• What You Will Learn:
• Real-world ML benchmarking workflows from model to hardware.
• Performance tuning and optimization techniques.
• How ML applications are tested, validated, and productized.
• Collaboration across software, hardware, and research teams.
• Tenstorrent offers a highly competitive compensation package and benefits, and we are an equal opportunity employer.

Additional Information

Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. As a Machine Learning Applications & Benchmarking Intern, your role will focus on benchmarking machine learning models on various hardware, creating clean code demos, building end-to-end applications, and ensuring the reliability of our software releases. This role is on-site based in Santa Clara, CA.

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Company Intel

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