Senior AI Application Engineer: Heterogeneous Compute Lead

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

Benefits offered by this job

Pension plan

Extensive employee insurances

Company shares

Open culture and inclusive environment

Job summary

Axelera AI is hiring a Senior/Staff Software Engineer to build the model enablement platform for Metis/Europa AIPU. You will architect and implement across frontend, graph compiler, runtime, and application pipeline, collaborating with AI agents and field engineers.

You will own model ingestion, heterogeneous execution, and end-to-end performance optimization, with exposure to devices from CPU to GPUs and NPUs. A strong emphasis on coding with C++/Python and MLIR-based tooling is essential.

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: reusable tools to partition, compile, run and profile; environments with access to real hardware; closed-loop runs that apply a change, measure it against the reference and repeat; and verification (differential testing, regression detection) integrated into CI.
• Model ingestion: Own how a PyTorch or ONNX model is captured, analysed and split across the AIPU's matrix and RISC-V vector units, the host CPU and the host's accelerators (GPU, NPU, video decoder), with placement tags that users can read and override. Build this with the graph compiler team so it works for every model.
• Heterogeneous execution: Extend that split to large models, cascades and multi-model pipelines, for example with expert offloading and caching across device and host memory. Agree the plan with the graph compiler team.
• End-to-end performance: With the application team (pipeline builder) and the runtime team, bring each model to its best end-to-end performance: overlap of host and device work, zero-copy buffers, batching, multi-core scheduling, and models with several inputs. Profile device time, host time and data movement, and confirm each speedup in the full pipeline.
• Critical models: Study the models that matter most to customers, on Metis today and on Europa, and turn each lesson into a platform improvement.

Skills

8+ years engineering

Heterogeneous computing

C++ and Python

ML graph concepts

AI agent workflows

Graph compiler

Tools

MLIR

TVM

XLA

TorchInductor

ONNX Runtime

Job description

Axelera AI is hiring a Senior/Staff Software Engineer to build the model enablement platform for Metis/Europa AIPU. You will architect and implement across frontend, graph compiler, runtime, and application pipeline, collaborating with AI agents and field engineers.

You will own model ingestion, heterogeneous execution, and end-to-end performance optimization, with exposure to devices from CPU to GPUs and NPUs. A strong emphasis on coding with C++/Python and MLIR-based tooling is essential.