Senior Compiler Engineer — Neuromorphic AI Accelerators

Innatera Nanosystems; Delft; On-site; EUR 90,000 - 120,000; Full time

Job summary

Innatera Nanosystems is seeking a Senior Compiler Engineer to advance the compiler framework for their neuromorphic AI accelerator at the edge. You will own end-to-end compiler development and partner with SDK, algorithm, architecture, and hardware teams to maximize performance and energy efficiency on our chip.

The role requires strong Python and C++ skills, experience with MLIR/TVM, and hands-on work with PyTorch or TensorFlow.

Qualifications

• Design and implement the compiler for next-generation AI accelerator architectures.
• Collaborate cross-functionally with SDK team members as well as algorithm, architecture, and hardware teams to gather compiler requirements.
• Provide feedback to hardware engineers to refine future architectural designs based on insights gained from compiler optimizations.
• Stay at the forefront of neural network compiler technologies, introducing innovative solutions and industry best practices to the team.

Responsibilities

• Design and implement the compiler for next-generation AI accelerator architectures.
• Collaborate cross-functionally with SDK team members as well as algorithm, architecture, and hardware teams to gather compiler requirements.
• Provide feedback to hardware engineers to refine future architectural designs based on insights gained from compiler optimizations.
• Stay at the forefront of neural network compiler technologies, introducing innovative solutions and industry best practices to the team.

Skills

Python

C++

Neural networks

PyTorch

TensorFlow

MLIR/TVM

Computer architecture

Prototyping

Communication

Tools

MLIR

TVM

GCC/LLVM

Job description

Innatera Nanosystems is seeking a Senior Compiler Engineer to advance the compiler framework for their neuromorphic AI accelerator at the edge. You will own end-to-end compiler development and partner with SDK, algorithm, architecture, and hardware teams to maximize performance and energy efficiency on our chip.

The role requires strong Python and C++ skills, experience with MLIR/TVM, and hands-on work with PyTorch or TensorFlow.