AI is growing faster than any technology in history and the explosion in demand has created a massive infrastructure gap; we can no longer build chips or power stations fast enough to keep up. The industry is still leaning on a ten-year-old hardware blueprint that has reached its limit. A new paradigm that is faster and more efficient will be the biggest economic opportunity of the next century and create the most important company of the next decade. The OLIX Decode Accelerator 1 (DX-1) is the first accelerator architected specifically for decode. Rack-scale co-design of logic, data movement, packaging, optics and interconnect enables a step change in system level performance.
We’re searching for Senior Compiler Engineer to join the team building the ML backend (compiler, run-time, and debugger) for our next-generation hardware that connect PyTorch, Tensorflow, JAX, and MXNet down to our low-level kernel drivers. Your mission will be to create seamless support for a broad ecosystem of large AI models, and ensure we are pushing the limits of their performance envelope by closely partnering with hardware and modelling teams to understand device trade-offs.
Due to U.S. export control regulations, candidates’ eligibility to work at OLIX depends on their most recent citizenship or permanent residency status. We are generally unable to consider applicants whose most recent citizenship or permanent residence is in certain restricted countries (currently including Iran, North Korea, Syria, Cuba, Russia, Belarus, China, Hong Kong, Macau, and Venezuela). Applicants who have subsequently obtained citizenship or permanent residency in another country not subject to these restrictions may still be eligible.
The latest generation of AI models achieve breakthrough performance by using vastly more tokens to solve complex problems. As frontier models become more sophisticated, demand is compounding faster than today’s infrastructure can scale.
Even the most dominant players, with full-stack control across silicon, software, and supply chains, are unable to solve this within the existing architecture. Inherent constraints in physical design and packaging mean a GPU-based approach is incapable of simultaneously delivering high throughput and high interactivity at low cost. Continuing AI’s advance and making it available to everyone requires a new compute paradigm. One that can overcome the fundamental limits of memory, energy, and speed that define today’s systems.
If you like working on difficult and consequential problems, we want you at OLIX. We have offices in London, Austin, Toronto, and Bristol.
Check out our careers page at olix.com/careers
