About Tensordyne (formerly Recogni)
AI is transforming our world. It can perform cognitive functions that previously only humans could do, such as perceiving interactions across different modalities and environments - with the ability to quickly learn and then solve complex problems. Tensordyne is an AI system solution company that builds very high-performance, low-power generative AI inference systems. Our mission, through the creation of custom silicon, hardware and software, is to enable multimodal Generative AI inference acceleration at scale, with safe, sustainable, high-performance systems for our hyperscaler and neocloud data center customers. We are at the leading edge of advancing the latest research and product improvements for generative Al inference solutions that will make Al even more advantageous for compelling new generative AI applications.Tensordyne is a well funded, fast-paced startup company with headquarters in both Sunnyvale, CA, and Munich, Germany. We also have many talented team members working remotely across North America and Europe. We take care of our people and their families with comprehensive benefits, competitive compensation, flexible spending options, and recognition programs, because building category-defining technology starts with a healthy, supported team. Come join us as we shape the future of multimodal generative artificial intelligence!
About the role
As a Software Engineer working within the Low-Level Runtime team, you will build components of an ML model execution framework – low-level assembler architecture hyper-optimized for our hardware – as well as port components of various models to be executed within it.
In this role, you will
- Maintain and develop low-level ML model execution framework in Rust
- Maintain and enhance components and whole models written for our hardware
- Optimize performance of ML models, maximizing performance and utlization
- Debug and productize models in both virtual and physical hardware environments
Preferred qualifications
- Experience with Rust programming language
- General awareness of high-level ML model concepts: LLMs, attention architectures
- Experience with low-level code development – e.g. embedded systems
- Experience with driving agents and building LLM engineering workflows
Nice to have
- Experience with Google Cloud Platform or similar
- Experience with Python
- Deep knowledge of modern LLM attention architectures (GDN, DSA, KDA etc)
Tensordyne is an equal opportunity employer. We believe that a diverse team is better at tackling complex problems and coming up with innovative solutions. All qualified applicants will receive consideration for employment without regard to age, color, gender identity or expression, marital status, national origin, disability, protected veteran status, race, religion, pregnancy, sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances.
A note to Recruitment Agencies: Please don’t reach out to Tensordyne employees or leaders about our roles -- we’ve got it covered. We don’t accept unsolicited agency resumes and we are not responsible for any fees related to unsolicited resumes. Thank you for your understanding.
Skills Required
- Rust programming language
- Maintain and develop low-level ML model execution framework
- Port and enhance ML models for custom hardware
- Optimize performance and utilization of ML models
- Debug and productize models in virtual and physical hardware environments
- General awareness of high-level ML model concepts (LLMs, attention architectures)
- Experience with low-level code development (embedded systems)
- Experience with driving agents and building LLM engineering workflows
- Google Cloud Platform (GCP)
- Python
- Deep knowledge of modern LLM attention architectures (GDN, DSA, KDA)
What We Do
Every leap in AI has followed the same pattern: first we made models bigger, then we tailored them, and now we let them think longer. Each step (scaling law) truly adds intelligence. But in the end we land on the same runway: inference, and demand is exploding while power supply lags. We asked: what if the next step isn’t stacking another law on top, but a zeroth law beneath them all. A law that changes AI math. Because after all, AI is math, trillions of multiplies, and multiplication burns watts. Tensordyne uses logarithmic compute to turn multiplies into adds, cutting power at the root. We’ve cast our proprietary logarithmic math into custom silicon, hardware, interconnect, and system software. The result: one integrated system for multimodal GenAI inference designed for Hyperscaler and Neo Cloud data centers. What this means for our customers: With Tensordyne they can run the world’s largest multimodal models for thousands of users, with fewer racks, less power, and lower cost. We’re well-funded and fast-moving, with co-headquarters in Sunnyvale, California and Munich, Germany, and a distributed team across North America and Europe. Join us to change how the world runs Gen AI.
