Senior AI Application Engineer – LLM, VLM Enablement

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🔥 0 minutes ago

🇳🇱 Netherlands – Remote

⏰ Full Time

🟠 Senior

💻 Application Engineer

👻 Ghost score 13%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Axelera AI

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2021

🏭 Manufacturing

💼 Consulting

📦 Logistics

Manufacturing • Consulting • Logistics

Axelera AI is a leading provider of AI hardware acceleration technology tailored for generative AI and computer vision inference. The company offers advanced AI processing units designed to integrate seamlessly into innovations, focused on delivering high-performance, cost-effective, and energy-efficient AI solutions. Axelera AI's flagship product, the Metis AI Processing Unit, accelerates inference at the edge, making it ideal for applications like video analysis and multi-channel video analytics. The company is recognized for its deep tech innovations and is actively contributing to the advancement of AI by providing state-of-the-art AI acceleration capabilities for edge computing.

📋 Description

• Own LLM and VLM support on Metis and Europa AIPUs, from studying new models to shipping them in the Voyager SDK • Study new LLM and VLM families and architectures, prototype and profile them on Metis and Europa, and determine how they should run on the hardware • Turn research results into supported Voyager SDK features with stable APIs, tests, documentation and release gates • Own PyTorch references with quantization, weight mappings, and contracts covering inputs, outputs, weights and persistent state • Hand model-side contracts to the compiler team and ensure runtime and tests use the same definitions • Integrate LLM and VLM serving into the Voyager SDK pipeline builder, including prefill, decode, KV-cache management, streaming text output and multimodal inputs • Measure accuracy against floating-point references and close or explain gaps • Extend the model enablement platform for LLM and VLM bring-up, including compiler/runtime/hardware environments, closed-loop runs and evaluations • Recommend Voyager SDK capabilities for GenAI, agents and speech on edge devices, and identify representative model-zoo demos • Use AI coding agents to build, test and verify work

🎯 Requirements

• 5+ years of software engineering experience • At least 2 years on ML inference, ML systems or ML tooling • Solid understanding of transformer inference, including attention variants, KV caching, prefill versus decode, sampling, tokenization, and VLM vision-language integration • Working knowledge of LLM quantization, including weight-only and weight-activation schemes, calibration, and outlier handling • Ability to distinguish quantization loss from an implementation bug • Strong Python and PyTorch skills • Experience shipping production-quality software • Daily use of AI coding agents on real codebases, with judgment to verify or reject their output • Ability to turn research code and hardware constraints into practical designs • Preferred: experience with inference engines or serving stacks such as llama.cpp, vLLM, ONNX Runtime GenAI, or ExecuTorch • Preferred: kernel development, tensor compilers such as Triton, TVM or MLIR, or profiling models on accelerator hardware • Preferred: speech (ASR, TTS) or agentic applications on embedded devices • Preferred: evaluation or testing harnesses for ML systems or AI agents, or tool-calling agents such as MCP servers

🏖️ Benefits

• Attractive compensation package • Pension plan • Extensive employee insurances • Option to get company shares • Flexible working arrangement • Open culture supporting creativity and continual innovation • Collaborative ownership and freedom with responsibility • Equal-opportunity, warm and inclusive environment