How do I apply for the INTERNSHIP Comparative study of AI workloads 2026 position at SiPearl and track my application?

We provide a direct link to the official application portal. You can apply directly here . Additionally, you can easily track this and other applications by clicking the bookmark icon to save it to your YGI Kanban board .

What are the working arrangements and expected duration for the INTERNSHIP Comparative study of AI workloads 2026 role?

This position is a not disclosed, structured as a not disclosed role, with an expected duration of 6 months.

What educational background or degree level is required for the INTERNSHIP Comparative study of AI workloads 2026 at SiPearl?

Candidates are generally expected to be holding or pursuing the following degree levels: Master.

Does SiPearl provide visa sponsorship or assistance for international applicants?

Regarding visa assistance and sponsorship for this role, the official status is currently listed as: Not disclosed.

INTERNSHIP Comparative study of AI workloads 2026

SiPearl

Found 1 month ago

Location

Castelldefels, Spain

Duration (Months)

6 Months

Time

Not disclosed

Work Mode

Not disclosed

Salary

Not disclosed

Visa Help

Not disclosed

Last Verified

1 month ago

Education

Master

Skills & Qualifications

Technical Skills

C
C++
Python
TensorFlow
PyTorch
ONNX Runtime
ARM architecture

Soft Skills

Understanding of machine learning workflows, including training, inference, and fine-tuning.
Knowledge of parallelization techniques for high-performance computing.
Familiarity with modern AI models and machine learning concepts.

Job Description

SiPearl is developing high-performance processors dedicated to European supercomputers. In this context, the intern will contribute to the optimization of HPC and AI workloads by leveraging advanced architectural features such as Scalable Vector Extension (SVE) vectorization and heterogeneous memory systems. During this internship, you will: * Evaluate the maturity of the AI software stack used for benchmarking, including frameworks such as MLPerf and similar benchmarks. * Test and optimize various machine learning frameworks, including TensorFlow , PyTorch , and ONNX Runtime , as well as mathematical libraries and different parallelization strategies. * Conduct comparative performance studies on AArch64 and x86 architectures. * Perform performance analysis and projections for future generations of SiPearl processors.

Requirements

Student in the final year of an engineering school or pursuing a Master's degree in electronics, computer engineering, or a related field
Experience in programming with C, C++, and Python.
Experience with machine learning frameworks such as TensorFlow or PyTorch.
Understanding of machine learning workflows, including training, inference, and fine-tuning.
Knowledge of parallelization techniques for high-performance computing.
Familiarity with modern AI models and machine learning concepts.
Good written and spoken English

AI & Machine Learning

Applied Machine Learning

Languages

English

Nice to Haves

Knowledge of ARM architecture is a plus.

Apply Now

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