Machine Learning Intern/Co-op (Fall 2023)
Toronto, Palo Alto, San Francisco, London
Applications have closed
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Cohere
Cohere provides industry-leading large language models (LLMs) and RAG capabilities tailored to meet the needs of enterprise use cases that solve real-world problems.We've raised our Series B, signed a multi-year partnership with Google Cloud, and we are focused on bringing our technology to market. We will partner with customers so they can build natural language understanding and generation into their products with just a few lines of code.
We’re ambitious — we believe our technology will fundamentally transform how industries interact with natural language. And we have the technical chops to back it up - Cohere’s CEO, Aidan Gomez, is a co-author of the groundbreaking paper “Attention is all you need”, and was previously part of Google Brain. Our entire technical team is world-class.
We are focused on creating a diverse and inclusive work environment so that all of our team members can thrive. We welcome kind and brilliant people to our team, from wherever they come.
Why this role?Ship state of the art models to production.Design and implement novel research ideas.Build elegant training/deployment pipelines.Join us at a pivotal moment, shape what we build and wear multiple hats as an intern!
Please Note: To be eligible for this position you should be a student currently enrolled in a post-secondary program, available for a full-time 3-6 month internship, co-op, or research work term (starting in September or October). We have offices in Toronto, Palo Alto, and London but embrace being remote-first! There are no restrictions on where you can be located for this role.
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
- Publish your work in top-tier conferences and journals
- Learn from experienced senior machine learning technical staff
- Work closely with product teams to develop solutions
You may be a good fit if you have:
- 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
- Bonus: experience writing kernels for GPUs using CUDA
- Bonus: experience training on TPUs
- Bonus: papers at top-tier venues (such as NeurIPS, ICML, ICLR, AIStats, MLSys, JMLR, AAAI, Nature, COLING, ACL, EMNLP)
If some of the above doesn’t line up perfectly with your experience, we still encourage you to apply! If you consider yourself a thoughtful worker, a lifelong learner, and a kind and playful team member, Cohere is the place for you.
We value and celebrate diversity and strive to create an inclusive work environment for all. We welcome applicants of all kinds and are committed to providing an equal opportunity process. Cohere provides accessibility accommodations during the recruitment process. Should you require any accommodation, please let us know and we will work with you to meet your needs.
Our Perks: 🤝 An open and inclusive culture and work environment 🧑💻 Work closely with a team on the cutting edge of AI research 🍽 Free daily lunch 🦷 Full health and dental benefits, including a separate budget to take care of your mental health 🎨 Personal enrichment benefits towards arts and culture, fitness and well-being🏙 Remote-flexible, offices in Toronto, Palo Alto, and London and coworking stipend✈️ Paid vacation
Tags: AIStats APIs Autoregressive models CoHere CUDA EMNLP GCP Google Cloud ICLR ICML JAX JMLR LLMs Machine Learning NeurIPS NLP Pipelines Python Research Streaming TensorFlow Transformers
Perks/benefits: Career development Conferences Flex hours Flex vacation Health care Home office stipend Salary bonus
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