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 content generation, 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 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!
Please note that this is not a live role. We are grateful for your enthusiasm and interest in Cohere and encourage you to submit your resume for future consideration. Should a suitable position become available, we will review your application and reach out to discuss potential opportunities.
Why this role?
Design and implement novel research ideas, ship state of the art models to production, and maintain deep connections to academia. We have one of the highest ratio of compute to engineers in the world. We do not delineate strongly between engineering and research. Everyone will contribute to writing production code and conducting research depending on individual interest and organizational needs. We have all the compute, data, and talent available for you to do your best work.
Please Note: We have offices in Toronto, London, San Francisco and New York but also embrace being remote-friendly! There are no restrictions on where you can be located for this role.
As a Member of Technical Staff, you will:
Design, build and scale AI systems for serving our users.
Research, implement, and experiment with ideas on our supercompute and data infrastructure.
Learn from and work with the best researchers in the field.
You may be a good fit if you have:
Extremely strong software engineering skills.
Proficiency in Python and related ML frameworks such as Tensorflow, TF-Serving, JAX, and XLA/MLIR.
Experience writing kernels for GPUs using CUDA.
Experience using large-scale distributed training strategies.
Familiarity with autoregressive sequence models, such as Transformers.
Bonus: paper at top-tier venues (such as NeurIPS, ICML, ICLR, AIStats, MLSys, JMLR, AAAI, Nature, COLING, ACL, EMNLP).
* This is neither an exhaustive nor necessary set of attributes. Even if none of these apply to you, but you believe you will contribute to Cohere, please reach out. We have a wide variety of backgrounds at Cohere.
If some of the above doesn’t line up perfectly with your experience, we still encourage you to apply! If you want to work really hard on a glorious mission with teammates that want the same thing, 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.
Full-Time Employees at Cohere enjoy these Perks:
? An open and inclusive culture and work environment
??? Work closely with a team on the cutting edge of AI research
? Weekly lunch stipend, in-office lunches & snacks
? Full health and dental benefits, including a separate budget to take care of your mental health
? 100% Parental Leave top-up for 6 months for employees based in Canada, the US, and the UK
? Personal enrichment benefits towards arts and culture, fitness and well-being, quality time, and workspace improvement
? Remote-flexible, offices in Toronto, New York, San Francisco and London and co-working stipend
?? 6 weeks of vacation
Note: This post is co-authored by both Cohere humans and Cohere technology.
