Staff AI Platform Engineer – Heterogeneous Compute

Axelera AI; Netherlands; Hybrid; EUR 120,000 - 180,000; Full time

Benefits offered by this job

Pension plan

Company shares

Extensive employee insurances

Job summary

Axelera AI seeks a Staff AI Application Engineer to build a model enablement platform and manage how models run across Metis/Europa AIPU, host CPU and accelerators. You will work across frontend, graph compiler, runtime and application pipeline to optimize end-to-end performance.

The role combines architecture with hands-on work, covering frontend and graph, while a device-side engineer handles backend. Experience with AI agents in daily work is valued.

Qualifications

• 8+ years of engineering experience in systems, compilers, runtimes or performance, including system-level design ownership.
• Hands-on experience with heterogeneous computing across CPU, GPU, DSP, NPU or FPGA, including reasoning about compute, memory bandwidth, latency and data movement.
• Solid fundamentals in computer architecture, operating systems and parallel programming.
• Familiarity with ML graph representations and compiler concepts: graph capture (torch.export, FX, ONNX), lowering, operator fusion, partitioning, memory planning.
• Strong C++ and Python.
• Daily use of AI coding agents on real engineering work, with the judgment to review and test their output.

Responsibilities

• Model enablement platform and agent harness: Build the platform that engineers and AI agents use to bring up models, with reusable tools to partition, compile, run and profile; environments with access to real hardware; closed-loop runs that apply a change, measure it and repeat; and CI-integrated verification.

Skills

Systems and perf

Heterogeneous compute

Computer architecture

ML graph concepts

C++ & Python

AI agents usage

Tools

MLIR/TVM

Job description

Axelera AI seeks a Staff AI Application Engineer to build a model enablement platform and manage how models run across Metis/Europa AIPU, host CPU and accelerators. You will work across frontend, graph compiler, runtime and application pipeline to optimize end-to-end performance.

The role combines architecture with hands-on work, covering frontend and graph, while a device-side engineer handles backend. Experience with AI agents in daily work is valued.