Senior AI Application Engineer — Remote, Equity Options

Axelera AI; Toscana; Remote; EUR 90,000 - 130,000; Full time

Benefits offered by this job

Pension plan

Employee insurances

Company shares

Job summary

Axelera AI is seeking a Senior AI Application Engineer to own LLM and VLM support on Metis and Europa AIPUs, from studying models to shipping them in the Voyager SDK. The role blends software engineering with AI coding agents to build, test and verify work across hardware and software interfaces.

You will prototype, implement and test new architectures, productize features with stable APIs, tests and documentation, and work closely with ML researchers to drive practical, production-ready

Qualifications

• 5+ years software engineering, 2+ years ML inference.
• Transformer inference and KV caching knowledge.
• Python and PyTorch with production-quality software.
• Experience with AI coding agents on real codebases.
• Able to translate research to practical design.

Responsibilities

• Study new LLM/VLM architectures and prototype on Metis/Europa.
• Productize results into Voyager SDK features with stable APIs.
• Define contracts for LLM/VLM blocks and hand to compiler.
• Integrate LLM/VLM into Voyager SDK pipeline.
• Collaborate on accuracy and speed against references.
• Extend the model enablement platform with hardware tests.
• Recommend GenAI needs for Voyager SDK and edge demos.

Skills

Software engineering

ML inference

Transformer inference

Python

PyTorch

AI coding agents

Quantization

Model deployment

Tools

Llama.cpp

vLLM

ONNX Runtime GenAI

ExecuTorch

Triton

TVM

MLIR

Job description

Axelera AI is seeking a Senior AI Application Engineer to own LLM and VLM support on Metis and Europa AIPUs, from studying models to shipping them in the Voyager SDK. The role blends software engineering with AI coding agents to build, test and verify work across hardware and software interfaces.

You will prototype, implement and test new architectures, productize features with stable APIs, tests and documentation, and work closely with ML researchers to drive practical, production-ready