We are looking for best in class engineers to join our existing top-notch team. When you join Untether AI, you will be part of a team that designs, develops and verifies the software that interacts with our chip, collaborating with our hardware engineers and with fellow software engineers in the process. By creating software that fully realizes the capabilities of the hardware, you will help get AI inference to the general populace.
As part of this exceptional team, you are able to - and get excited by - identifying functional/performance bottlenecks and how to alleviate them in order to achieve scalable and reliable software. You excel in an environment with complex software and hardware designs.
***Please note: While our engineering HQ is in Toronto, this is a remote opportunity and we welcome applicants from anywhere in North America.***
We are looking for algorithm and optimization experts to help unlock the potential of Untether AI’s unique spatial compute architecture. In this role, you would develop efficient solutions to the hard graph optimization problems involved in allocating chip resources for neural network inference acceleration. These challenges include graph partitioning, scheduling, and place and route optimization. Additionally, you would develop profiling and visualization tools and collaborate with other teams in identifying performance bottlenecks and conceiving creative solutions.
Requirements
- Computer Science, Engineering, or related degree
- 5+ years of SW development experience
- Creative problem solver, passionate about solving hard problems
- Expertise in combinatorial and graph optimization algorithms
- Strong C++ and python development skills
- Experience optimizing code for high-performance and delivering it to production
- Excellent communication and collaboration skills
Preferred Skills & Experience
- Masters or PhD in Computer Science, Engineering, or related field
- EDA or FPGA place and route experience
- Relentless focus on software quality and testing
- Proficient with python data-science libraries (pandas, numpy, bokeh)
- Familiar with neural net frameworks tensorflow or pytorch
- Experience working with continuous integration systems
What are some of the perks that you will receive being part of Untether AI?
- Aligned to Untether’s philosophy, our employees enjoy the same perks, regardless of role or level. In part, these include:
- 20 vacation days
- Strong health and extended health benefits
- Unlimited sick days
- Stock options
- Building chips and software that will change the world
Thinking about applying?
- We’re a pretty welcoming bunch of people. If we’ve piqued your interest, you’re passionate about the same things we are but you aren’t sure if you check all the boxes, please apply anyway. We’re a great place to work, an even better place to learn and we focus on both capability and potential!
- Besides being a pretty friendly group, we’re also pretty diverse - ethnically, experientially and in our physical and mental abilities. If you are someone who needs accommodation during the interview process and/or in the workplace, please send a note along with your resume to [email protected] and we’ll be in touch.
A little bit more about Untether AI
Untether AI has developed a groundbreaking new architecture that brings neural net inference to new levels of performance and efficiency. We’ve already sold our product to smart clients who want to get in at ground zero. We’ve done this while continuing to improve our technology creating ultra-efficient, high performance AI chips that eliminates the data movement bottleneck that costs energy and performance in traditional architectures. We’re a team made up of scientists, engineers and entrepreneurs and have the support of tier one investors. We recently received $125 million in our series B funding round which enables us to expand our customer engagements, enhance our software offering, and build the next generation of industry leading AI inference products. Join us to be part of something big - a chance to create the future of AI.
