How do I apply for the ML Models Implementation & Performance Optimization, Intern position at tenstorrentuniversity 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 .

Is the internship at tenstorrentuniversity paid and what compensation can candidates expect?

Yes, this is a paid internship opportunity. Exact compensation details are typically finalized during the company interview process.

What are the working arrangements and expected duration for the ML Models Implementation & Performance Optimization, Intern role?

This position is a not disclosed, structured as a on-site role, with an expected duration of 3 months.

What educational background or degree level is required for the ML Models Implementation & Performance Optimization, Intern at tenstorrentuniversity?

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

Does tenstorrentuniversity 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.

ML Models Implementation & Performance Optimization, Intern

tenstorrentuniversity

Found 1 month ago

Location

Belgrade, Serbia

Duration (Months)

3 Months

Time

Not disclosed

Work Mode

On-site

Salary

highly competitive

Visa Help

Not disclosed

Last Verified

1 month ago

Education

Bachelor
Master

Skills & Qualifications

Technical Skills

Python
C++
machine learning
PyTorch
tt-metalium
tt-nn
tt-llk

Soft Skills

passion for programming
eager to learn
enjoy solving complex performance and optimization problems
collaborative
open to feedback
excited to work closely with experienced engineers
work closely with a dedicated mentor

Job Description

In this role, you will implement state of art ML models on Tenstorrent hardware using Python and C++, focusing on pushing both accuracy and inference speed. You will work hands-on with Tenstorrent’s open-source software stack (tt-metalium, tt-nn, tt-llk), taking models from framework to silicon and iterating on performance. You will own a well-defined engineering project under the guidance of a dedicated mentor, with direct impact on how real workloads run on our chips. We are looking for a minimum of 3 months for this role with the potential for extension to 6 months.

Requirements

Enrolled in the final year of BSc or MSc studies in Computer Science, Computer Engineering, Software Engineering, Electronics, Math, or a related field.
Solid coding skills in Python and C++, with a basic understanding of machine learning concepts and frameworks.
You have a passion for programming, are eager to learn, and enjoy solving complex performance and optimization problems.
You are collaborative, open to feedback, and excited to work closely with experienced engineers and a dedicated mentor.

AI & Machine Learning

Applied Machine Learning

Apply Now

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