Intern - ML Inference Performance Engineer

We're looking for a curious, rigorous engineer to join our team and dig into the performance of ML inference systems. You'll work across the full inference stack — from model export and compiler toolchains to runtime execution on silicon — to build a clear, evidence-based picture of how different platforms perform and why.

Your work will go beyond running benchmarks: you'll develop a repeatable evaluation methodology, investigate performance bottlenecks at the hardware and software level, and build the tooling that transforms raw measurements into actionable insight. The findings you produce can directly shape our product decisions.

Key responsibilities:

Benchmarking & Tooling: Develop a thorough understanding of internal benchmarking tools covering throughput, latency, power, and accuracy across device-level, host-transaction, and end-to-end pipeline scenarios. Improve existing tooling, define reproducible procedures, and establish a standardised results format for rigorous cross-platform comparisons. Maintain a dedicated dashboard for performance visualisations.

Platform Evaluation: Research and evaluate AI accelerator products from various vendors, gaining hands-on experience with their SDKs, toolchains, flexibility, and limitations through a structured evaluation process. Track model support across platforms to identify strengths, gaps, and areas for improvement.

Pipeline Analysis: Characterise full inference pipelines, capturing host-device transaction overhead and end-to-end performance metrics. Ensure equivalent pipeline configurations across platforms using frameworks such as GStreamer to maintain methodological consistency.

Lab & Infrastructure: Set up and maintain lab hosts across multiple hardware platforms and support the onboarding of new evaluation hardware.

Reporting: Synthesise findings into clear, structured reports that directly inform engineering and roadmap decisions.

Requirements:

Currently enrolled in the final years of a Bachelor's programme or in a Master's programme in Computer Engineering, Electrical Engineering, Computer Science, or a related field. This position may also be carried out as a Master's thesis project.

Python development experience

C/C++ knowledge

Experience with end-to-end computer vision pipelines

Familiarity with benchmarking concepts (performance, latency, etc.)

Experience with inference tools, APIs, or SDKs (e.g., TensorRT)

Familiarity with deep learning model concepts (quantization, ONNX, PyTorch, etc.)

Development experience using agentic AI

Knowledge of version control (Git)

Familiarity with LLM benchmarking concepts

Proficiency with Linux, Bash scripting, and Docker

Hands-on experience with embedded hosts

Proficient written and verbal communication skills in English, with the ability to document findings clearly and precisely.

Good organizational skills

Nice to have:

GStreamer knowledge

Basic GUI design experience

Location

Work from our Axelera AI office in Eindhoven (Netherlands).

What we offer 

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.