Inference Server – Product Software Intern (Oct 2026 start)

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.

At Tenstorrent, we believe the future of computing must be open, which is why our interns don’t just watch from the sidelines - they help build the core of it.

We provide a "code-to-career" pipeline where students collaborate with industry experts to solve high-stakes problems in RISC-V and AI hardware-software co-design.

By joining us, you are taking an internship to democratize high-performance computers that are accessible to everyone.

Join our Inference Server Technologies team, where we build the software layer that powers state-of-the-art AI inference on Tenstorrent hardware.

This team develops APIs, deploys workloads, and benchmarks end-to-end model performance so developers can efficiently scale inference on our stack.

You will work on a project under the guidance of experienced engineers and a dedicated mentor.

We are looking for a minimum of 3 months for this role with the potential for extension to 6 months.

• Final-year BSc or MSc student in Computer Science, Software Engineering, Electrical Engineering, or a related technical field
• Strong programming fundamentals in Python, with familiarity in C++ considered a plus
• Interested in backend systems, API design, and how ML models are deployed in production environments
• Curious about performance optimization techniques such as batching, caching, and model parallelism
• Motivated to learn and contribute in a collaborative engineering environment
• Contribute to backend features and APIs that support AI inference workloads
• Assist in deploying, testing, and benchmarking models running on Tenstorrent hardware
• Analyze inference performance and help identify optimization opportunities