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!
Why this role?
As a Member of Technical Staff on our Applied ML team, you will work directly with customers to quickly understand their greatest problems and design and implement solutions using Large Language Models.
You’ll apply your problem-solving ability, creativity, and technical skills to close the last-mile gap in Enterprise AI adoption. You’ll be able to deliver products like early startup CTOs/CEOs do and disrupt some of the most important industries and institutions globally!
As a Senior Member of Technical Staff, you will:
Plan and execute large-group projects that carry through from ideation to production.
Bring cross-functional alignment across engineering, product and other disciplines.
Mentor a distributed team of engineers in subject matter expertise.
Identify opportunities and gaps in existing models and strategize what to work on.
Work closely with product teams to develop solutions.
Engage in collaborations with our partner organizations.
Assist our legal teams with preparation of patents on developed IP.
Join us at a pivotal moment, shape what we build and wear multiple hats!
You may be a good fit if you have:
Prior experience in leading ML teams in applied research and production.
Prior experience in setting as well as executing technical direction to build new or to refine existing products.
Prior experience in working cross-discipline in matrixed organizations.
Proficiency in Python and related ML frameworks such as Tensorflow, TF-Serving, JAX, and XLA/MLIR.
Experience using large-scale distributed training and inference.
Strong mentorship, communication, and problem-solving skills.
A demonstrated passion for applied ML models and products.
Working proficiency in Japanese.
Bonus: experience working for B2B companies in the ML space.
* 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.
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