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- Tasks: Optimise performance of advanced language models and systems for AI training.
- Company: Cohere is on a mission to scale intelligence for humanity through innovative AI solutions.
- Benefits: Enjoy remote flexibility, weekly lunch stipends, full health benefits, and 6 weeks of vacation.
- Why this job: Join a passionate team at the forefront of AI research and make a real impact.
- Qualifications: Strong software engineering skills, proficiency in Python, and experience with GPU kernels required.
- Other info: Diversity is celebrated; all backgrounds are encouraged to apply.
The predicted salary is between 36000 - 60000 £ per year.
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 Performance Engineer in the Pre-Training team you will be responsible for optimizing the performance of our advanced language models and systems. Their primary focus is on improving key model training metrics, such as training throughput, ensuring high accelerator utilization.
The team combines expertise in software engineering, machine learning, and low-level kernel design and development to design robust systems and enhance model performance. You will work on identifying and removing performance bottlenecks, develop cutting-edge training and profiling tools to help Cohere\’s mission of providing efficient and reliable language understanding and generation capabilities and drive innovation in the field of natural language processing.
Please Note: We have offices in London, 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:
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Design and write high-performant and scalable software for training.
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Understand architectural modifications and design choices and their effects on training throughput and quality.
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Write low-level CUDA, triton kernels to squeeze every last bit of performance from our accelerators.
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Research, implement, and experiment with ideas on our supercompute and data infrastructure.
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Learn from and work with the best researchers in the field.
You may be a good fit if you have:
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Extremely strong software engineering skills.
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Proficiency in Python and related ML frameworks such as JAX, Pytorch and XLA/MLIR.
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Experience writing kernels for GPUs using CUDA, triton, etc
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Experience using large-scale distributed training strategies.
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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).
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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Member of Technical Staff, Training Performance Engineer employer: Cohere
Contact Detail:
Cohere Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Member of Technical Staff, Training Performance Engineer
✨Tip Number 1
Familiarise yourself with the latest advancements in AI and natural language processing. Understanding the current trends and technologies will not only help you during interviews but also demonstrate your passion for the field.
✨Tip Number 2
Engage with the community by attending relevant conferences or webinars. Networking with professionals in the industry can provide valuable insights and potentially lead to referrals, which can significantly boost your chances of landing the job.
✨Tip Number 3
Showcase your technical skills through personal projects or contributions to open-source initiatives. This practical experience can set you apart from other candidates and give you concrete examples to discuss during interviews.
✨Tip Number 4
Prepare for technical interviews by practising coding challenges and system design problems related to performance engineering. Being well-prepared will help you feel more confident and capable of demonstrating your expertise.
We think you need these skills to ace Member of Technical Staff, Training Performance Engineer
Some tips for your application 🫡
Understand the Role: Before applying, make sure to thoroughly read the job description for the Member of Technical Staff, Training Performance Engineer position. Understand the key responsibilities and required skills, especially in software engineering, machine learning, and CUDA programming.
Tailor Your CV: Customise your CV to highlight relevant experience and skills that align with the job requirements. Emphasise your proficiency in Python, ML frameworks, and any experience with GPU kernels or distributed training strategies.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for AI and your understanding of Cohere's mission. Mention specific projects or experiences that demonstrate your ability to optimise performance and contribute to innovative solutions.
Showcase Your Achievements: If you have published papers or contributed to significant projects in the field of AI or machine learning, be sure to include these in your application. Highlighting your achievements can set you apart from other candidates.
How to prepare for a job interview at Cohere
✨Showcase Your Technical Skills
Be prepared to discuss your software engineering skills in detail. Highlight your experience with Python, CUDA, and any relevant ML frameworks like JAX or PyTorch. Bring examples of projects where you've optimised performance or written low-level kernels.
✨Understand the Company’s Mission
Familiarise yourself with Cohere's mission to scale intelligence for humanity. Be ready to explain how your role as a Performance Engineer aligns with their goals of enhancing AI capabilities and improving model training metrics.
✨Prepare for Technical Questions
Expect technical questions related to distributed training strategies and autoregressive sequence models. Brush up on your knowledge of Transformers and be ready to discuss how you would approach performance bottlenecks in model training.
✨Demonstrate Your Passion for AI
Cohere values passion and dedication. Share your enthusiasm for AI and natural language processing, and if applicable, mention any research papers you've authored or contributed to in top-tier venues. This will show your commitment to the field.
