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- Tasks: Design and write scalable software for training AI models and improve their performance.
- Company: Cohere is on a mission to scale intelligence for humanity through cutting-edge AI technology.
- Benefits: Enjoy remote flexibility, health benefits, weekly lunches, and 6 weeks of vacation.
- Why this job: Join a diverse team pushing the boundaries of AI research and development.
- Qualifications: Strong software engineering skills, proficiency in Python, and experience with distributed training infrastructures.
- Other info: Open to applicants from all backgrounds; diversity is celebrated at Cohere.
The predicted salary is between 48000 - 84000 £ per year.
Join us on our mission and shape the future!
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.
Why this role?
Advance the state of the art for model post training, ship state of the art models to production, and bridge the gap between research and production. We have one of the highest ratios of compute to engineers in the world. We do not delineate strongly between engineering and research. Everyone will contribute to writing production code and supporting our research effort depending on individual interest and organisational needs. We have all the compute, data, and talent available for you to do your best work.
Please Note: We have offices in London, Paris, Toronto, San Francisco, 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 and write high-performant and scalable software for training models.
- Consistently post-train the models to reach SOTA level performance.
- Coordinate with other specialist teams (Agentic, Code…) to produce models that have strong all-encompassing performance.
- Craft and implement techniques to improve the performance and results of our training cycles both on the SFT and the RL regime.
- 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 JAX, Pytorch and XLA/MLIR.
- Experience with distributed training infrastructures (Kubernetes, Slurm) and associated frameworks (Ray).
- Experience using large-scale distributed training strategies.
- Hands-on experience on training large models at scale.
- Hands-on experience with the post-training phase of model training, with a strong emphasis on performance optimisation.
- 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.
Member of Technical Staff, Post training team employer: Cohere
Contact Detail:
Cohere Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Member of Technical Staff, Post training team
✨Tip Number 1
Familiarise yourself with the latest advancements in AI and machine learning, particularly in post-training techniques. This will not only help you understand the role better but also allow you to engage in meaningful conversations during interviews.
✨Tip Number 2
Network with current or former employees of Cohere on platforms like LinkedIn. They can provide valuable insights into the company culture and expectations, which can be beneficial when preparing for your interview.
✨Tip Number 3
Showcase your hands-on experience with distributed training infrastructures and large-scale model training. Be ready to discuss specific projects or challenges you've faced, as this will demonstrate your practical knowledge and problem-solving skills.
✨Tip Number 4
Prepare to discuss how you can contribute to bridging the gap between research and production. Think of examples from your past work where you've successfully implemented research findings into practical applications.
We think you need these skills to ace Member of Technical Staff, Post training team
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your software engineering skills, particularly in Python and ML frameworks like JAX and Pytorch. Emphasise any experience with distributed training infrastructures and large-scale model training.
Craft a Compelling Cover Letter: In your cover letter, express your passion for AI and how your background aligns with Cohere's mission. Mention specific projects or experiences that demonstrate your ability to contribute to post-training model performance.
Showcase Relevant Experience: If you have hands-on experience with the post-training phase of model training, make sure to detail this in your application. Highlight any performance optimisation techniques you've implemented in past roles.
Highlight Collaborative Skills: Cohere values teamwork, so mention any collaborative projects you've worked on, especially those involving cross-functional teams. This will show your ability to coordinate effectively with other specialists.
How to prepare for a job interview at Cohere
✨Showcase Your Technical Skills
Make sure to highlight your strong software engineering skills, especially in Python and ML frameworks like JAX and PyTorch. Be prepared to discuss specific projects where you've implemented these technologies, as this will demonstrate your hands-on experience.
✨Understand the Role's Requirements
Familiarise yourself with the specifics of the post-training phase of model training. Be ready to discuss techniques you've used for performance optimisation and how you can contribute to advancing state-of-the-art models.
✨Demonstrate Collaboration Skills
Since the role involves coordinating with other specialist teams, be prepared to share examples of how you've successfully collaborated in past projects. This could include working with cross-functional teams or contributing to research efforts.
✨Express Your Passion for AI
Cohere values a passion for AI and its applications. Share your enthusiasm for the field and any relevant research or projects you've been involved in. If you have published papers, mention them as they can set you apart from other candidates.
