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System Software Engineer - RAG Job Opening In Redmond – Now Hiring NVIDIA


Job description

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!

The base salary range is 180,000 USD - 339,250 USD.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.

You will also be eligible for equity and .

NVIDIA accepts applications on an ongoing basis.

NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer.

As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

Required Skill Profession

Computer Occupations


  • Job Details

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Unlock Your System Software Potential: Insight & Career Growth Guide


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Are You Looking for System Software Engineer RAG Job?

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The fundamental ethical values are:

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2. Loyalty

3. Impartiapty

4. Integrity

5. Accountabipty

6. Respect for human rights

7. Obeying United States laws and regulations

What Is the Average Salary Range for System Software Engineer RAG Positions?

The average salary range for a varies, but the pay scale is rated "Standard" in Redmond. 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.

What Are the Key Qualifications for System Software Engineer RAG?

Key qualifications for System Software Engineer RAG typically include Computer Occupations and a list of qualifications and expertise as mentioned in the job specification. The generic skills are mostly outlined by the . Be sure to check the specific job listing for detailed requirements and qualifications.

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Interview Tips for System Software Engineer RAG Job Success

NVIDIA interview tips for System Software Engineer   RAG

Here are some tips to help you prepare for and ace your System Software Engineer RAG job interview:

Before the Interview:

Research: Learn about the NVIDIA's mission, values, products, and the specific job requirements and get further information about

Other Openings

Practice: Prepare answers to common interview questions and rehearse using the STAR method (Situation, Task, Action, Result) to showcase your skills and experiences.

Dress Professionally: Choose attire appropriate for the company culture.

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Plan Your Commute: Allow ample time to arrive on time and avoid feeling rushed.

During the Interview:

Be Punctual: Arrive on time to demonstrate professionalism and respect.

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Confidence and Enthusiasm: Project a positive attitude and show your genuine interest in the opportunity.

Answer Thoughtfully: Listen carefully, take a moment to formulate clear and concise responses. Highlight relevant skills and experiences using the STAR method.

Ask Prepared Questions: Demonstrate curiosity and engagement with the role and company.

Follow Up: Send a thank-you email to the interviewer within 24 hours.

Additional Tips:

Be Yourself: Let your personality shine through while maintaining professionalism.

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Be Positive: Focus on your strengths and accomplishments.

Body Language: Maintain good posture, avoid fidgeting, and make eye contact.

Turn Off Phone: Avoid distractions during the interview.

Final Thought:

To prepare for your System Software Engineer RAG interview at NVIDIA, research the company, understand the job requirements, and practice common interview questions.

Highlight your leadership skills, achievements, and strategic thinking abilities. Be prepared to discuss your experience with HR, including your approach to meeting targets as a team player. Additionally, review the NVIDIA's products or services and be prepared to discuss how you can contribute to their success.

By following these tips, you can increase your chances of making a positive impression and landing the job!

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