Intern - ML Inference Performance Engineer

Position Overview

We're looking for a curious, rigorous Intern - ML Inference Performance 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.

Role details

• Location: Eindhoven (hybrid)
• Employment Type: Full time
• Location Type: Hybrid
• Department: Customer Engineering & Success

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

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.