Senior Solutions Architect Generative AI Data Processing
NVIDIA
Job Overview
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Job Description
About NVIDIA
NVIDIA is seeking outstanding AI Solutions Architects to assist and support customers that are building solutions with our newest AI technology. At NVIDIA, our solutions architects work across different teams and enjoy helping customers with the latest Accelerated Data Analytics and Deep Learning software and hardware platforms. We're looking to grow our company and build our teams with the smartest people in the world. Would you like to join us at the forefront of technological advancement?
You will become a trusted technical advisor with our customers, work on exciting projects and deploy AI solutions in production using Data Processing for Generative AI. You will also collaborate with a diverse set of internal teams on innovative AI optimization techniques, operating at the intersection of algorithms and systems. You should be comfortable working in a dynamic environment, and have experience with Deep Learning, LLMs and GPU technologies. This role is an excellent opportunity to work in an interdisciplinary team at NVIDIA!
What You Will Be Doing
- Partnering with other solution architects, engineering, product, and business teams. Understanding their strategies and technical needs and helping define high-value solutions
- Dynamically engaging with developers, scientific researchers, and data scientists, gaining experience across a range of technical areas
- Strategically partnering with lighthouse customers and industry-specific solution partners targeting our computing platform
- Working closely with customers to help them adopt and build creative solutions using NVIDIA technology
- Design and implement scalable systems to accelerate agentic workflows and efficiently handle datacenter-scale use cases
- Some travel to conferences and customers may be required
What We Need To See
- BS, MS, or PhD in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, other Engineering or related fields (or equivalent experience)
- 8+ years of hands-on experience with Machine Learning, Deep Learning, and Data Analytics
- Strong fundamentals in programming, optimizations, and software design, especially in Python
- Strong problem-solving and debugging skills
- Experience with containerization and orchestration technologies, monitoring, and observability solutions for AI deployments
- Excellent presentation, communication, and collaboration skills
Ways To Stand Out From The Crowd
- Prior experience with AI at scale on cloud environments (e.g., AWS, Azure, GCP) and on-premises infrastructure
- Experience with NVIDIA GPUs and software libraries, such as NVIDIA NeMo Framework, NeMo Retriever, cuVS, RAPIDS
- Expertise in MLOps including Kubernetes, Docker, Helm charts, Jupyter notebooks
- Excellent C/C++ programming skills, including debugging, profiling, code optimization, performance analysis, and test design
- Familiarity with parallel programming and distributed computing platforms
Key skills/competency
- Generative AI
- Deep Learning
- Large Language Models (LLMs)
- GPU Technologies
- Data Analytics
- Python Programming
- Containerization
- Kubernetes
- MLOps
- Cloud Computing
How to Get Hired at NVIDIA
- Research NVIDIA's culture: Study their mission, values, recent news, and employee testimonials on LinkedIn and Glassdoor to align with the company's innovation-driven environment.
- Tailor your resume for Generative AI: Customize your resume to highlight experience in Deep Learning, LLMs, GPU technologies, and data processing, using keywords found in the Senior Solutions Architect Generative AI Data Processing job description.
- Showcase technical prowess: Prepare to discuss your hands-on experience with Machine Learning, Python programming, containerization, and MLOps, demonstrating strong problem-solving and optimization skills.
- Emphasize communication and collaboration: For a Senior Solutions Architect Generative AI Data Processing role at NVIDIA, effective presentation, communication, and cross-functional collaboration are crucial for engaging with customers and internal teams.
- Network and prepare for technical depth: Connect with current NVIDIA employees on LinkedIn for insights, and be ready for in-depth technical discussions on AI at scale, cloud environments, and distributed computing platforms during interviews.
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