At a Glance
- Tasks: Optimise advanced language models and enhance training performance with cutting-edge tools.
- Company: Join a leading tech firm at the forefront of natural language processing.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Collaborate with top researchers and enjoy a dynamic, innovative work environment.
- Why this job: Make a real impact in AI by improving model performance and driving innovation.
- Qualifications: Strong software engineering skills, proficiency in Python, and experience with ML frameworks.
The predicted salary is between 60000 - 80000 € per year.
Requirements
- Extremely strong software engineering skills
- Proficiency in Python and related ML frameworks such as JAX, Pytorch and XLA/MLIR
- Experience writing kernels for GPUs using CUDA, triton, etc
- Experience using large-scale distributed training strategies
- Familiarity with autoregressive sequence models, such as Transformers (Desirable)
- 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!
What the job involves
- 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.
- Design and write high-performant and scalable software for training.
- Understand architectural modifications and design choices and their effects on training throughput and quality.
- Write low-level CUDA, triton kernels to squeeze every last bit of performance from our accelerators.
- Research, implement, and experiment with ideas on our supercompute and data infrastructure.
- Learn from and work with the best researchers in the field.
Member of Technical Staff (Training Performance Engineer) in London employer: Deepstreamtech
Cohere is an exceptional employer for those passionate about advancing natural language processing, offering a dynamic work culture that fosters innovation and collaboration. Located in a vibrant tech hub, employees benefit from access to cutting-edge resources, opportunities for professional growth, and the chance to work alongside leading experts in the field. With a strong emphasis on employee development and a commitment to pushing the boundaries of technology, Cohere provides a rewarding environment for technical talent to thrive.
StudySmarter Expert Advice🤫
We think this is how you could land Member of Technical Staff (Training Performance Engineer) in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with potential colleagues on LinkedIn. We all know that sometimes it’s not just what you know, but who you know!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Python, CUDA, or ML frameworks. We love seeing real-world applications of your expertise, so make sure to highlight any relevant work you've done.
✨Tip Number 3
Prepare for technical interviews by brushing up on your coding skills and understanding performance optimisation techniques. We recommend practicing with platforms that focus on algorithms and system design to get you in top shape.
✨Tip Number 4
Don’t hesitate to apply through our website! Even if you don’t tick every box in the job description, we encourage you to throw your hat in the ring. Your unique experiences might just be what we’re looking for!
We think you need these skills to ace Member of Technical Staff (Training Performance Engineer) in London
Some tips for your application 🫡
Show Off Your Skills:Make sure to highlight your software engineering skills and any experience with Python and ML frameworks like JAX or Pytorch. We want to see what you've got, so don’t hold back!
Tailor Your Application:Customise your application to reflect how your experience aligns with the role. If you’ve worked on GPU kernels or distributed training strategies, let us know! We love seeing relevant examples.
Don’t Sweat the Small Stuff:If you don’t tick every box in the job description, don’t worry! We encourage you to apply anyway. Your unique experiences might just be what we’re looking for.
Apply Through Our Website:For the best chance of getting noticed, make sure to apply through our website. It’s the easiest way for us to keep track of your application and get back to you quickly!
How to prepare for a job interview at Deepstreamtech
✨Show Off Your Coding Skills
Make sure to brush up on your Python skills and be ready to demonstrate your proficiency with ML frameworks like JAX and PyTorch. You might be asked to solve coding problems or discuss your previous projects, so have examples ready that showcase your software engineering prowess.
✨Know Your Kernels
Since the role involves writing low-level CUDA and Triton kernels, be prepared to discuss your experience in this area. Bring specific examples of how you've optimised performance in past projects, and be ready to explain the impact of your work on training throughput and model quality.
✨Familiarise Yourself with Transformers
While familiarity with autoregressive sequence models is desirable, it’s a good idea to brush up on the latest developments in Transformers. Be ready to discuss how these models work and any relevant research you’ve done, especially if you have papers published at top-tier venues.
✨Ask Insightful Questions
Interviews are a two-way street, so prepare some thoughtful questions about the team’s current projects and challenges. This shows your genuine interest in the role and helps you gauge if the company aligns with your career goals.
