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- Tasks: Implement and optimise cutting-edge deep learning models across various domains and frameworks.
- Company: Join NVIDIA, a leader in AI technology, known for innovation and excellence.
- Benefits: Enjoy a full-time role with opportunities to work on unreleased hardware and remote options.
- Why this job: Make a real impact in AI while collaborating with top engineers in a dynamic environment.
- Qualifications: 3+ years in deep learning, strong Python skills, and experience with frameworks like PyTorch required.
- Other info: NVIDIA values diversity and creativity, offering a supportive workplace for all.
The predicted salary is between 43200 - 72000 £ per year.
Senior Deep Learning Engineer, Deep Learning Algorithms
Join to apply for the Senior Deep Learning Engineer, Deep Learning Algorithms role at NVIDIA
Senior Deep Learning Engineer, Deep Learning Algorithms
Join to apply for the Senior Deep Learning Engineer, Deep Learning Algorithms role at NVIDIA
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Direct message the job poster from NVIDIA
We are looking for senior engineers who are mindful of performance analysis and optimization to help us squeeze every last clock cycle out of Deep Learning training, inference and NVIDIA AI Services. We are working across all layers of the hardware/software stack, from GPU architecture, Deep Learning Frameworks all the way up to large scale computing and orchestration, , to achieve peak performance. This role offers an opportunity to directly impact the hardware and software roadmap in a fast-growing company that leads the AI revolution.
Join the team building software used by the entire world. Work with world class software engineers to implement blazingly fast SOTA deep learning models that help understanding the end-to-end performance of NVIDIA’s DL software and hardware stack. Work on most powerful, enterprise-grade GPU clusters capable of hundreds of Peta FLOPS and on unreleased hardware before anyone in the world.
Are you ready for this challenge?
What You’ll Be Doing
- Implement deep learning models from multiple data domains (CV, NLP/LLMs, ASR, TTS, RecSys and others) in multiple DL frameworks (PyT, JAX, TF2, DGL and others)
- Implement and test new SW features (Graph Compilation, reduced precision training) that use the most recent HW functionalities.
- Analyze, profile, and optimize deep learning workloads on state-of-the-art hardware and software platforms.
- Collaborate with researchers and engineers across NVIDIA, providing guidance on improving the design, usability and performance of workloads.
- Lead best-practices for building, testing, and releasing DL software.
- Contribute to creation of large scale benchmarking system, capable of testing thousands of models on vast diversity of hardware and software stacks.
What We Need To See
- 3+ years of experience in DL model implementation and SW Development.
- BSc, MS or PhD degree in Computer Science, Computer Architecture or related technical field.
- Excellent Python programming skills.
- Extensive knowledge of at least one DL Framework (PyTorch, TensorFlow, JAX, MxNet) with practical experience in PyTorch required.
- Strong problem solving and analytical skills.
- Algorithms and DL fundamentals.
- Docker containerization fundamentals.
Ways To Stand Out From The Crowd
- Experience in performance measurements and profiling.
- Experience with containerization technologies such as Docker.
- GPU programming experience (CUDA or OpenCL) is a plus but not required.
- Knowledge and love for DevOps/MLOps practices for Deep Learning-based product’s development.
- Experience with CI systems (preferably GitLab).
NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most brilliant and forward-thinking people in the world working for us. If you\’re creative and autonomous, we want to hear from you! We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
JR2001639
Seniority level
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Seniority level
Mid-Senior level
Employment type
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Employment type
Full-time
Job function
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Industries
Computer Hardware Manufacturing, Software Development, and Computers and Electronics Manufacturing
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Senior Deep Learning Engineer, Deep Learning Algorithms employer: Nvidia
Contact Detail:
Nvidia Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Deep Learning Engineer, Deep Learning Algorithms
✨Tip Number 1
Familiarise yourself with NVIDIA's latest hardware and software offerings. Understanding their GPU architecture and deep learning frameworks will give you an edge in discussions during interviews.
✨Tip Number 2
Engage with the deep learning community by contributing to open-source projects or forums. This not only showcases your skills but also helps you network with professionals who might have insights into NVIDIA's hiring process.
✨Tip Number 3
Prepare to discuss specific performance optimisation techniques you've implemented in past projects. Being able to articulate your problem-solving approach will demonstrate your expertise and fit for the role.
✨Tip Number 4
Consider reaching out to current or former NVIDIA employees on LinkedIn. They can provide valuable insights about the company culture and what the interview process is like, helping you tailor your approach.
We think you need these skills to ace Senior Deep Learning Engineer, Deep Learning Algorithms
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in deep learning model implementation and software development. Emphasise your proficiency in Python and any specific frameworks like PyTorch, TensorFlow, or JAX.
Craft a Strong Cover Letter: Write a cover letter that showcases your passion for deep learning and AI. Mention specific projects or experiences that demonstrate your problem-solving skills and familiarity with performance analysis and optimisation.
Highlight Relevant Skills: In your application, clearly outline your experience with Docker, GPU programming, and CI systems. These skills are particularly valued for this role, so make them stand out.
Showcase Collaboration Experience: Since the role involves working with researchers and engineers, include examples of past collaborations. Highlight how you contributed to improving design, usability, and performance in previous projects.
How to prepare for a job interview at Nvidia
✨Showcase Your Deep Learning Expertise
Be prepared to discuss your experience with deep learning models in detail. Highlight specific projects where you've implemented models using frameworks like PyTorch or TensorFlow, and be ready to explain the challenges you faced and how you overcame them.
✨Demonstrate Performance Optimisation Skills
Since the role focuses on performance analysis and optimisation, come equipped with examples of how you've profiled and optimised deep learning workloads. Discuss any tools or techniques you've used to enhance performance on hardware platforms.
✨Familiarise Yourself with NVIDIA's Technology
Research NVIDIA's current hardware and software offerings, especially their GPU architecture and AI services. Understanding their technology will allow you to speak knowledgeably about how your skills can contribute to their goals.
✨Prepare for Technical Questions
Expect technical questions related to algorithms, deep learning fundamentals, and containerization technologies like Docker. Brush up on these topics and be ready to solve problems on the spot, as this will demonstrate your analytical skills.
