Runtime Engineer

Role: Runtime Engineer

Location: SF Bay Area / Toronto | Full-time | Hybrid

Compensation: Competitive salary (based on experience & location) + Equity + Bonus

This is your opportunity to join a mission-driven startup building the foundation of sustainable AI. The team is creating a high-performance compiler and runtime that allows developers to “build once, deploy anywhere”—from the cloud to the edge—while optimizing efficiency and scalability.

As a Runtime Engineer, you will focus on developing multi-target runtime systems, leveraging advanced techniques in concurrency, parallelization, and hardware optimization. Your work will directly shape the performance and accessibility of next-generation AI infrastructure.

• Design, develop, and optimize multi-target runtime systems.
• Use modern techniques in parallelization and partitioning to generate highly efficient kernels.
• Rapidly prototype and explore new approaches using data-driven methods.
• Benchmark and analyze compiler outputs across diverse hardware platforms.
• Collaborate with product teams to align runtime design with ML engineers’ needs.
• Build tools to identify, analyze, and resolve performance bottlenecks.

• Strong expertise in asynchronous and concurrent programming.
• 4+ years of experience with C/C++ (C++14 or newer).
• Solid understanding of hardware architectures (vector vs scalar registers, memory hierarchies).
• Experience with OS kernel or hypervisor development.

• Experience with CUDA, ROCm, or GPU programming.
• Background in HPC (high-performance computing).
• Advanced degree (MS/PhD) in Computer Science or related field.
• Familiarity with deep learning frameworks (PyTorch, JAX, Triton).
• Experience programming for large compute clusters.

• Salary:
  Competitive, adjusted for experience and geography.
• Equity + performance-based bonus opportunities.
• Medical, dental, and vision coverage.
• Retirement savings plan.
• Supplemental wellness benefits.
• Hybrid flexibility (SF Bay Area or Toronto).

• Build core AI infrastructure – work on runtime systems that power sustainable, scalable AI.
• Cutting-edge engineering – apply advanced concurrency, GPU programming, and HPC techniques.
• Mission-driven culture – focus on innovation with environmental responsibility.
• High-growth environment – contribute to core architecture at a pivotal stage for the company.