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Machine Learning Intern/Co-op (Fall 2024) image - Rise Careers
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Machine Learning Intern/Co-op (Fall 2024)

Who are we? Our mission is to scale intelligence to serve humanity. We’re training and deploying frontier models for developers and enterprises who are building AI systems to power magical experiences like semantic search, RAG, and agents. We believe that our work is instrumental to the widespread adoption of AI... We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. We like to work hard and move fast to do what’s best for our customers. Cohere is a team of researchers, engineers, designers, and more, who are passionate about their craft. Each person is the one of the best in the world at what they do. We believe that a diverse range of perspectives is a requirement for building great products. Join us on our mission and shape the future! 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! Our recruitment process will begin in the upcoming weeks, and we will be carefully reviewing applications and assessing potential candidates for our internships. Should we find a suitable match with your qualifications and our requirements, we will be in touch to discuss the opportunity further and to advance your application to the next stage. Please apply by June 28th. 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. We have offices in Toronto, San Francisco, New York, and London but embrace being remote-friendly! 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. • 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 from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form, and we will work together 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, New York, San Francisco and London and coworking stipends ✈️ Paid vacation
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Cohere, founded by AI pioneers, offers a leading enterprise AI platform that combines ease-of-use, data privacy, and unparalleled flexibility with its cloud-agnostic and API-accessible services,

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DATE POSTED
June 8, 2024

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