ML Research Intern (Co-op) — Train Large Models (Remote)

Feedinkoo; United States; Hybrid; USD 41,000 - 58,000; Full time

Benefits offered by this job

Open and inclusive culture

Team on the cutting edge of AI

Weekly lunches; health and dental

Remote‑flexible offices in multiple US

Six weeks vacation

Job summary

Cohere is seeking a Machine Learning Intern to contribute to cutting‑edge model development and production deployment. You will train and refine state‑of‑the‑art NLP models, work on scalable training techniques, and collaborate with researchers, engineers, and product teams to deliver robust AI solutions.

The internship offers exposure to large‑scale systems, ongoing research, and mentorship from senior staff, with remote‑flexible offices across multiple major cities.

Qualifications

• Must be currently enrolled in a post-secondary program (full‑time).
• Internship duration: 3–6 months, full‑time or equivalent co‑op/research work term.
• Strong Python and ML framework skills required; experience with large‑scale training is a plus.

Responsibilities

• Design, train, and improve cutting‑edge models.
• Develop techniques for safer, faster model training and serving.
• Train very large-scale models on massive datasets.
• Explore continual and active learning strategies for streaming data.
• Collaborate with product teams to deliver AI solutions.

Skills

Python

ML frameworks

Distributed training

Transformers

Communication

Applied NLP

CUDA (bonus)

TPU (bonus)

Research mindset

Education

Post-secondary student

Tools

TensorFlow

TF-Serving

JAX

XLA/MLIR

CUDA

TPU

Job description

Cohere is seeking a Machine Learning Intern to contribute to cutting‑edge model development and production deployment. You will train and refine state‑of‑the‑art NLP models, work on scalable training techniques, and collaborate with researchers, engineers, and product teams to deliver robust AI solutions.

The internship offers exposure to large‑scale systems, ongoing research, and mentorship from senior staff, with remote‑flexible offices across multiple major cities.