Intern - ML Inference Performance Engineer

3 нед. назад

НидерландыTraineeHybrid

ml inferenceperformance analysisbenchmarking

Internship role focused on performance engineering of ML inference systems across the entire stack from model export to runtime execution.

AI is not your regular deep-tech company. We are creating the next-generation AI platform to support anyone who wants to help advancing humanity and improve the world around us.
In just five years, we have raised a total of $370 million and have built a world-class team of 250+ employees (including 60+ PhDs with more than 40,000 citations), both remotely from 20 different countries and with offices in Belgium, France, Switzerland, Italy, the UK, headquartered at the High Tech Campus in Eindhoven, Netherlands.
We have also launched our Metis™ AI Platform, which achieves a 3-5x increase in efficiency and performance, and have visibility into a strong business pipeline exceeding $100 million.
Our unwavering commitment to innovation has firmly established us as a global industry pioneer.
Are you up for the challenge?

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.

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

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

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.