Senior AI Application Engineer - LLM & VLM Enablement

This is your chance to shape and be part of a dynamic, fast-growing, international organization. We offer an attractive compensation package, including a pension plan, extensive employee insurances and the option to get company shares.

An open culture that supports creativity and continual innovation is awaiting you. Collaborative ownership and freedom with responsibility is characteristic for the way we act and work as a team.

At Axelera AI, we wholeheartedly embrace equal opportunity and hold diversity in the highest regard. Our steadfast commitment is to cultivate a warm and inclusive environment that empowers and celebrates every member of our team. We welcome applicants from all backgrounds to join us in shaping the future of AI.

As a Senior AI Application Engineer in the Model Enablement team (Application Software), you will own LLM and VLM support on Metis and Europa AIPUs, from studying new models to shipping them in the Voyager SDK.

The role combines LLM/VLM knowledge with solid software engineering. Our team uses AI coding agents in daily work, and you will use them to build, test and verify your own work.

We also welcome experienced field application engineers, technical leads and engineering managers who want to return to hands-on engineering. Experience in planning, delegating and reviewing work transfers well to working with AI agents.

• LLM/VLM study: Study new LLM and VLM families and architectures (for example mixture-of-experts, small VLMs, new attention and decoding schemes). Prototype and profile them on Metis and Europa, and decide how they should run on our hardware.

• Productization: Turn your results and our ML research group's results into supported Voyager SDK features, with stable APIs, tests, documentation and release gates.

• Model-side contracts: For each LLM/VLM building block, own the PyTorch reference with quantization baked in, the weight mapping, and one contract that lists every input, output, weight and persistent state (such as a paged KV cache), and hand that contract to the compiler team. The runtime and tests use the same definition.

• Pipeline integration: Bring LLM and VLM serving into the Voyager SDK pipeline builder: prefill and decode, KV-cache management, streaming text output and multimodal inputs.

• Quality: With the regression and quantization owners, measure accuracy against the floating-point reference, and close or explain each gap.

• LLM/VLM bring-up platform: Extend the model enablement platform for LLM and VLM bring-up: environments with access to the compiler, runtime and real hardware (for example through MCP tools), closed-loop runs that apply a change, measure accuracy and speed against the reference and repeat, and evaluations that score each run.

• GenAI direction: Recommend what the Voyager SDK needs for GenAI, agents and speech on edge devices, and which model zoo demos show it best.

We offer a flexible working arrangement, with options to:

• Work from one of our Axelera AI offices (Leuven in Belgium, Amsterdam and Eindhoven in the Netherlands, Zurich in Switzerland, Florence and Milan in Italy or Bristol in the United Kingdom) if you're already based in the vicinity.

• Work fully remotely from any European country (incl. the UK) you are already in.

• Relocate with us and work from Italy (Florence or Milan) or the Netherlands (Amsterdam or Eindhoven).

Kindly note that priority will be given to candidates who are [interested in being] based in Belgium or Italy.