How do I apply for the Machine Learning Intern/Co-op position at Cohere 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 Machine Learning Intern/Co-op role?

This position is a full-time, structured as a remote role, with an expected duration of 4.5 months.

What educational background or degree level is required for the Machine Learning Intern/Co-op at Cohere?

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

Does Cohere 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.

Machine Learning Intern/Co-op

Cohere

Found 1 month ago

Location

Remote, Canada

Duration (Months)

4.5 Months

Time

Full-time

Work Mode

Remote

Salary

Not disclosed

Visa Help

Not disclosed

Last Verified

1 month ago

Education

Bachelor

Skills & Qualifications

Technical Skills

Python
Tensorflow
TF-Serving
JAX
XLA/MLIR
large-scale distributed training strategies
autoregressive sequence models
Transformers
applied NLP models

Soft Skills

communication skills
problem-solving skills

Job Description

As a Machine Learning Intern, you will: Design, train and improve upon cutting-edge models. Help us develop new techniques to train and serve models safer, better, and faster. Train extremely large-scale models on massive datasets. Explore continual and active learning strategies for streaming data. Learn from experienced senior machine learning technical staff. Work closely with product teams to develop solutions.

Requirements

student currently enrolled in a post-secondary program
available for a full-time 3-6 month internship, co-op, or research work term
Proficiency in Python and related ML frameworks such as Tensorflow, TF-Serving, JAX, and XLA/MLIR
Experience using large-scale distributed training strategies
Familiarity with autoregressive sequence models, such as Transformers
Strong communication and problem-solving skills
A demonstrated passion for applied NLP models and products

AI & Machine Learning

Applied Machine Learning

Languages

English

Nice to Haves

experience writing kernels for GPUs using CUDA
experience training on TPUs
papers at top-tier venues (such as NeurIPS, ICML, ICLR, AIStats, MLSys, JMLR, AAAI, Nature, COLING, ACL, EMNLP)

Apply Now

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