Urgent! System Software Engineer - RAG Job Opening In Santa Clara – Now Hiring NVIDIA
NVIDIA's technology is at the heart of the AI revolution, touching people across the planet by powering everything from self-driving cars, robotics, co-pilots and more.
Join us at the forefront of technological advancement in intelligent assistants and information retrieval.
What Is Retrieval-Augmented Generation, aka RAG?
Retrieval-augmented generation (RAG) is a technique for enhancing the accuracy and reliability of generative AI models with facts fetched from external sources.
NVIDIA is looking for a System Software Engineer - RAG to develop pipelines for indexing and querying multi-modal content.
We are looking for someone with a passion for working with the world's most complicated problems in Generative AI, LLM, MLLM, and RAG spaces using our innovative hardware and software platforms.
You will develop tools for building powerful, flexible, multi-modal retrievers and agents driven by Large Language Models(LLM) thereby improving the experience of millions of customers.
If you're creative & passionate about solving real world conversational AI problems, come join us.
What You'll Be Doing:
Develop and optimize Python-based data processing frameworks, ensuring efficient handling of large datasets on GPU-accelerated environments, vital for LLM training.
Contribute to the design and implementation of RAPIDS and other GPU-accelerated libraries, focusing on seamless integration and performance enhancement in the context of LLM training data preparation and RAG pipelines.
Lead development and iterative optimization of components for RAG pipelines, ensuring they demonstrate GPU acceleration & the best performing models for improved TCO.
Collaborate with teams of LLM & ML researchers in the development of full-stack, GPU-accelerated data preparation pipelines for multimodal models Implement benchmarking, profiling, and optimization of innovative algorithms in Python in various system architectures, specifically targeting LLM applications.
Work closely with complementary teams to understand requirements, build & evaluate POCs, and develop roadmaps for production level tools and library features within the growing LLM ecosystem.
Build amazing products to improve employee productivity using Gen-AI & Co-pilot experiences!
Collaborate with your peers to craft, develop, test, and maintain integrated applications and features.
Develop integrated systems enabling unified experience across applications and driving insights for end-to-end user experience.
Help build and maintain our Continuous Delivery pipeline with the goal of moving changes to production faster and safer, while ensuring key operational standards.
Provide peer reviews to other specialists including feedback on performance, scalability, and correctness.
Actively contribute to the adoption of frameworks, standards, and new technologies
What We Need To See:
Bachelor’s or Master’s Degree program in Computer Science, Computer Engineering, or a related field (or equivalent experience).
6+ years of demonstrated experience in a similar or related role
Python programming expertise with Deep Learning (DL) frameworks such as PyTorch.
Experience delivering software in a cloud context and is familiar with the patterns and process of handling cloud infrastructure
Knowledge of MLOps technologies such as Docker-Compose, Containers, Kubernetes, data center deployments etc.
Excellent in-depth hands-on understanding of NLP, LLM, MLLM, Generative AI , and RAG workflows
Self-starter with a passion for growth, enthusiasm for continuous learning and sharing findings across the team
Extremely motivated, highly passionate, and curious about new technologies.
Outstanding communication skills for distilling sophisticated topics down to understandable, impactful conclusions as well as the ability to work successfully with multi-functional teams, principals, and architects.
Coordinates optimally across organizational boundaries and geographies.
If you are passionate about technology, have a proven track record in system software engineering, and are eager to make a significant impact in the industry, we would love to hear from you.
Join us at NVIDIA and help us craft the future of visual computing!
You will also be eligible for equity and .
NVIDIA accepts applications on an ongoing basis.
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Unlock Your System Software Potential: Insight & Career Growth Guide
Real-time System Software Jobs Trends in Santa Clara, United States (Graphical Representation)
Explore profound insights with Expertini's real-time, in-depth analysis, showcased through the graph below. This graph displays the job market trends for System Software in Santa Clara, United States using a bar chart to represent the number of jobs available and a trend line to illustrate the trend over time. Specifically, the graph shows 50484 jobs in United States and 1148 jobs in Santa Clara. This comprehensive analysis highlights market share and opportunities for professionals in System Software roles. These dynamic trends provide a better understanding of the job market landscape in these regions.
Great news! NVIDIA is currently hiring and seeking a System Software Engineer RAG to join their team. Feel free to download the job details.
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An organization's rules and standards set how people should be treated in the office and how different situations should be handled. The work culture at NVIDIA adheres to the cultural norms as outlined by Expertini.
The fundamental ethical values are:The average salary range for a System Software Engineer RAG Jobs United States varies, but the pay scale is rated "Standard" in Santa Clara. Salary levels may vary depending on your industry, experience, and skills. It's essential to research and negotiate effectively. We advise reading the full job specification before proceeding with the application to understand the salary package.
Key qualifications for System Software Engineer RAG typically include Computer Occupations and a list of qualifications and expertise as mentioned in the job specification. Be sure to check the specific job listing for detailed requirements and qualifications.
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Before the Interview:To prepare for your System Software Engineer RAG interview at NVIDIA, research the company, understand the job requirements, and practice common interview questions.
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