Are you looking for a Job at Cohere in Toronto, ON
in 2022. Then following info is about this job.
About the job
Who are we?
We’re a small, diverse team working at the cutting edge of machine learning. At Cohere, our mission is to build machines that understand the world and to make them safely accessible to all. Language is at the crux of this, but it can be difficult and expensive to parse the syntax, semantics, and context that all work together to give words meaning. The Cohere platform provides access to Large Language Models through its APIs that read billions of web pages and learn to understand the meaning, sentiment, and intent of the words we use in a richness never seen before.
We recently 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” , (over 23k citations) 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?
Cohere is dedicated to lowering the barriers to entry to machine learning research and supporting a community of independent research talent across the world. We are committed to collaborating widely and empowering independent researchers around the world.
As a Machine Learning Education Lead, you have an independent high impact research agenda and are excited to work with researchers from all over the world. You actively contribute to the wider research community by sharing and publishing your findings and code. Your work demonstrates consideration for the societal and ethical implications of machine learning. You have a strong track record of mentorship and are excited to collaborate with independent researchers around the world who are new to the machine learning and NLP community.
Please Note: We have offices in Toronto, Canada, and Palo Alto, USA, but embrace being remote-first! There are no restrictions on where you can be located for this role.
As a Machine Learning Education Lead, you will have:
- Ph.D. or equivalent research experience
- Peer-reviewed publications in machine learning, AI, computer science, statistics, applied mathematics, data science, or related technical fields
- Strong machine learning and NLP fundamentals
You may be a good fit if you:
- Enjoy collaborating widely
- Have a track record of mentorship and are excited to democratize access to machine learning
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 welcome applicants of all kinds and are committed to providing both an equal opportunity process and work environment. We value and celebrate diversity and strive to create an inclusive work environment for all.
? 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 for employees based in Canada and the US, including a separate budget to take care of your mental health
? 100% Parental Leave top-up for 6 months for employees based in Canada and 12 weeks in the US
? Personal enrichment benefits towards arts and culture, fitness and well-being, quality time, and workspace improvement
? Remote-flexible, offices in Toronto and Palo Alto and coworking stipend
✈️ 6 weeks of vacation and shared Canada/US holidays
Vacancy Type: Full-time · Associate
Job Location: Toronto, ON
Application Deadline: N/A
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