Machine Learning Intern/Co-op (Winter 2024)

Who are we? We're a small, diverse team operating at the forefront of machine learning. At Cohere, our objective is to produce machines that comprehend the world and make them safely accessible to everyone. Language forms the heart of this venture, but parsing the syntax, semantics, and context that gives words their meaning can be challenging and costly. The Cohere platform offers access to Large Language Models through its APIs that read billions of web pages and learn to discern the meaning, sentiment, and purpose of the words we use in an unprecedented richness. We've recently completed our Series C funding round and are focusing on introducing our technology to the market. We aim to collaborate with customers to allow them to integrate natural language understanding and generation into their products with just a few lines of code. Our ambition is wide-ranging — we believe our technology will revolutionize how industries interact with natural language. With Cohere’s CEO, Aidan Gomez, a co-author of the groundbreaking paper “Attention is all you need”, and with previous experience at Google Brain, we have the technical expertise to back it up. Our entire technical team is world-class. We're dedicated to creating a diverse and inclusive work environment where all members of our team can flourish. We welcome kind and brilliant individuals to our team, regardless of where they're from. Why this role? You will send state-of-the-art models to production, design and implement innovative research ideas, construct sophisticated training/deployment pipelines, and join us at a pivotal moment to shape what we build and wear multiple hats as an intern! Please Note: Eligibility for this position requires you to 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 (January - April). We have offices in Toronto, Palo Alto, and London but we are primarily remote-based. There are no location restrictions for this role. As a Machine Learning Intern, your responsibilities will include: Designing, training, and improving upon cutting-edge models, helping us develop new techniques to train and serve models safer, better, and faster, training large-scale models on massive datasets, exploring continual and active learning strategies for streaming data, publishing your work in top-tier conferences and journals, learning from experienced senior machine learning technical staff, and working closely with product teams to develop solutions. You may be a good fit if you possess: Proficiency in Python and related ML frameworks such as Tensorflow, TF-Serving, JAX, and XLA/MLIR, experience using large-scale distributed training strategies, a familiarity with autoregressive sequence models like Transformers, strong communication and problem-solving skills, a demonstrated passion for applied NLP models and products and experience writing kernels for GPUs using CUDA or training on TPUs or have papers at top venues, such as NeurIPS, ICML, ICLR, AIStats, MLSys, JMLR, AAAI, Nature, COLING, ACL, EMNLP. We still urge you to apply even if some of the criteria above doesn't align perfectly with your experience! 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, aiming to create an inclusive work environment for all. We welcome applicants of all backgrounds and are committed to equal opportunity procedures. Cohere provides accessibility accommodations during the recruitment process, so if you require any assistance, please inform us, and we will work with you to meet your needs. Our Perks: An open and inclusive culture and work environment, the opportunity to 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 manage your mental health, personal enrichment benefits towards arts and culture, fitness, and well-being, remote-flexibility, offices in Toronto, Palo Alto, and London and a coworking stipend, and paid vacation.