Compiler Code Gen Engineer

About Us

At the company, we're reimagining the foundations of computing to make AI accessible to everyone. Our mission is to remove the limits of scale, hardware, and cost that hold back innovation, so the people solving humanity's hardest problems can move faster.

We're building a new kind of software stack: a hardware-agnostic platform that makes every system — from a laptop to a supercomputer — feel like one seamless engine. Developers can write once, run anywhere, and get state-of-the-art performance across any chip, any cloud, at any scale. It's a complete rethink of how software and hardware interact — designed for the era beyond Moore's Law.

We're not looking for the comfortable or the conventional; we're looking for the bold. The engineers who crave frontier problems, who want to bend the limits of what's possible, who see infrastructure not as a constraint but as a canvas. If you want to build the foundation for the next era of AI and change what humanity can achieve in the process, join us.

About the Role

We're looking for a Compiler Code Generation Engineer to design and build the core code generation capabilities inside our high-performance, portable AI compiler. This is a foundational engineering role where you'll work directly on the subsystems that translate high-level ML computations into optimized machine code across heterogeneous hardware targets.

If you love digging into instruction selection, register allocation, and low-level target-specific optimization and you want that work to matter at the scale of the next era of AI infrastructure, this role is for you.

What You'll Do

• Design, develop, maintain, and improve our heterogeneous AI compiler.

• Design and implement new code generation capabilities based on our novel compiler architecture.

• Propose improvements and extensions to our compiler architecture in response to advances in ML model design and hardware.

• Apply the latest techniques in parallelization and partitioning to automate kernel generation and exploit highly optimized execution paths.

• Use performance data to identify optimization opportunities and drive measurable improvements.

• Collaborate with our product team to understand the evolving needs of ML engineers and translate those needs into architectural improvements.

Requirements

Essential Skills and Experience

• BS degree in Computer Science, Computer Engineering, Electrical Engineering, or equivalent practical experience.

• 4+ years of experience working with compilers.

• Deep knowledge of compiler algorithms and data structures.

• Experience with and genuine interest in low-level code generation, object file manipulation, and target-specific optimizations.

• 4+ years of experience with C/C++.

• Strong written and verbal communication skills; ability to write clear and concise technical documentation.

Preferred Skills and Experience

• Master's or PhD in Computer Science, Computer Engineering, Electrical Engineering, or equivalent.

• Knowledge of traditional compiler techniques: instruction selection, register allocation, dominance analysis, def-use chains.

• Familiarity with calling conventions, APIs, linking, and relocations.

• Working knowledge of LLVM.

• Experience with loop optimizations, vectorization, unrolling, fusion, and parallelization.

• Experience with machine learning workloads and their hardware demands.

Why Join the company

• Work on compiler infrastructure that runs AI at scale across every major hardware platform.

• Tackle deep, unsolved technical problems alongside a team that prizes craft and rigor.

• Be part of building sustainable AI infrastructure that genuinely moves the needle.

• Competitive compensation including equity, medical/dental/vision, retirement savings, and wellness benefits.

The company is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees, regardless of gender identity, race, ethnicity, sexual orientation, disability status, age, or background.

Compensation depends on experience and geographic location and will be narrowed during the interview process. Additional benefits include equity, company bonus opportunities, medical, dental, and vision coverage, a retirement savings plan, and supplemental wellness benefits.