How do I apply for the Compiler Engineer Intern (Neural Engine) position at Counting the Apples 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 Compiler Engineer Intern (Neural Engine) role?

This position is a not disclosed, structured as a not disclosed role.

What educational background or degree level is required for the Compiler Engineer Intern (Neural Engine) at Counting the Apples?

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

Does Counting the Apples 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.

Compiler Engineer Intern (Neural Engine)

Counting the Apples

Found 3 weeks ago

Location

Munich, Germany

Time

Not disclosed

Work Mode

Not disclosed

Salary

Not disclosed

Visa Help

Not disclosed

Last Verified

3 weeks ago

Education

Bachelor

Skills & Qualifications

Technical Skills

C++
C
Swift
compiler development
ML models

Soft Skills

communication skills

Job Description

As an intern compiler engineer in the Apple Neural Engine Software team, you will be - Explore and support techniques to accelerate early compiler development - Explore and support techniques to accelerate statically analyze program properties - Explore and support the develop compiler optimizations to improve latency/bandwidth of our ML models - Engage with QA teams

Requirements

Bachelor's
Some experience with compiler development
programming skills in C++, C or Swift
Proficiency in English

Software Engineering

Low Level System Software

Languages

English

Nice to Haves

low level software architecture
modeling
validation
AI networks for example CNN, transformer and diffusion model architectures and their performance characteristics
MLIR

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