ML Models Implementation & Performance Optimization - Intern (Serbia)

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.

If you want to immerse yourself in innovative technologies and you have a passion for programming, machine learning (ML), and performance optimization, this role is perfect for you!During your internship, you will implement state-of-the-art ML models on Tenstorrent hardware using Python and C++. Your primary goal is to achieve both high accuracy and fast execution (inference) of the models. You will use (and potentially debug and fix) existing Tenstorrent’s open-source software libraries, such as tt-metalium, tt-nn, and tt-llk.Throughout your internship, you will gain hands-on experience, collaborate with experienced engineers, learn various problem-solving techniques, and work on a well-defined engineering project under the guidance of a dedicated mentor.

This role is on-site at our Belgrade office.

Responsibilities:

• Implement functional ML models on Tenstorrent hardware using Python and popular ML frameworks like PyTorch.
• Benchmark, analyze, and optimize the performance of the implemented model's inference using existing tools and coding in C++ and Python.
• Validate the accuracy of the implemented models.

Experience & Qualifications:

• Enrolled in the final year of BSc or MSc studies in Computer Science, Computer Engineering, Software Engineering, Electronics, Math, or a related field.
• Solid coding skills in Python and C++.
• Basic understanding of machine learning concepts and frameworks.
• [Big plus] Experience with implementing ML models on GPUs or other accelerators.
• [Big plus] Interest in performance profiling and optimization.