Cohere · 1 day ago

Research Internship

United States

Internship

Remote

Intern

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Artificial Intelligence (AI)Generative AI

Comp. & Benefits

No H1B

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Responsibilities

Conduct cutting-edge machine learning research, building and training large language models.

Focus on research projects aimed at expanding the frontier of knowledge in language modelling and associate areas such as evaluation, multimodal models, optimisation etc.

Disseminate your research results through the production of publications, datasets, and code.

Contribute to research initiatives that have practical applications in Cohere’s product development.

Qualification

Find out how your skills align with this job's requirements. If anything seems off, you can easily click on the tags to select or unselect skills to reflect your actual expertise.

Machine LearningNLPLarge Language ModelsPythonCC++LuaJAXPytorchTensorflowDistributed TrainingData AnnotationEvaluation PipelinesTransformersDeep LearningAnalytical Problem SolvingResearch PublicationsQuantitative MethodologiesHigh-dimensional Data AnalysisApplied NLP

Required

Currently pursuing a PhD in Machine Learning, NLP, or a related discipline.

Available for a full-time internship that lasts for 4-6 months.

Eligible for work authorization in the country of employment at the time of hire and maintain ongoing work authorization throughout the internship period.

Experience using large-scale distributed training strategies, data annotation and evaluation pipelines, or implementing state of the art ML models.

Familiar with autoregressive sequence models, such as Transformers.

Strong communication and problem-solving skills with the ability to convey complex research findings clearly and succinctly.

Knowledge of programming languages such as Python, C, C++, Lua, or related languages.

Knowledge of related ML frameworks such as JAX, Pytorch and Tensorflow.

Previous experience in building systems based on machine learning and deep learning techniques.

Demonstrate passion for applied NLP models and products.

Preferred

Demonstrated expertise through publications in top tier venues in fields such as machine learning, NLP, artificial intelligence, computer vision, optimization, computer science, statistics, applied mathematics, or data science.

Proven ability to tackle analytical problems using quantitative methodologies.

Proficiency in handling and analysing complex, high-dimensional data from various sources.

Experience in applying theoretical and empirical research to real-world problem-solving.