The ideal candidate brings deep data center architecture experience, strong product and customer ... security in compute environments. Ways to stand out from the crowd: * Ability to work optimally ...
The ideal candidate brings deep data center architecture experience, strong product and customer ... security in compute environments. Ways to stand out from the crowd: * Ability to work optimally ...
... building data centers, and enabling other high-performance computing applications. We are ... Familiarity with CPU and SoC security architecture, such as ARM Confidential Compute * Experience ...
... building data centers, and enabling other high-performance computing applications. We are ... Familiarity with CPU and SoC security architecture, such as ARM Confidential Compute * Experience ...
Senior ML Platform Engineer
Boulder, CO · On-site
$108K - $148K/yr
... distributed compute systems. * Strong proficiency in Infrastructure-as-Code (IaC) tools ... Solid understanding of ML workflows and lifecycle-from data preprocessing to deployment.
Senior ML Platform Engineer
Boulder, CO · On-site
$108K - $148K/yr
... distributed compute systems. * Strong proficiency in Infrastructure-as-Code (IaC) tools ... Solid understanding of ML workflows and lifecycle-from data preprocessing to deployment.
Data Crowd Compute information
What is the highest paid job in data science?
In data science, the highest paid roles are typically senior positions such as Lead Data Scientist, Machine Learning Director, or Chief Data Officer, with salaries often exceeding $150,000 annually depending on experience, industry, and location. These roles require advanced skills in machine learning, statistical analysis, and leadership, often complemented by advanced degrees and certifications.
What are the typical challenges faced in a Data Crowd Compute position?
Professionals in Data Crowd Compute roles often handle vast volumes of data that require creative and efficient processing solutions, which can present scalability and performance challenges. Coordinating compute tasks across distributed environments demands attention to system reliability, cost optimization, and data integrity. Team members frequently collaborate with data scientists, engineers, and stakeholders to prioritize workloads and deliver timely results. Overcoming these challenges not only sharpens technical expertise but also positions you for advancement into senior or specialized technology roles.
Are data centers taking jobs?
Data centers themselves do not take jobs; rather, they provide infrastructure that supports various IT and technical roles. Jobs related to data centers include network administrators, technicians, and security specialists, often requiring technical skills and certifications. Employment in this sector depends on industry demand and company needs.
What is the highest paying data entry job?
The highest paying data entry jobs typically involve specialized roles such as medical or legal transcription, which require additional skills and certifications. These positions can offer higher hourly rates or salaries compared to standard data entry roles, especially when performed with advanced software or in niche industries.
Which 3 jobs will survive AI?
Data Crowd Compute roles, which involve labeling and validating data for AI training, are likely to persist as they require human judgment and oversight. Jobs in healthcare, such as nurses and medical technicians, will continue due to the need for empathy and complex decision-making. Additionally, skilled trades like electricians and plumbers are less susceptible to automation because of the physical and problem-solving skills involved.
What are the key skills and qualifications needed to thrive in the Data Crowd Compute position, and why are they important?
To thrive in a Data Crowd Compute role, you need a solid grounding in data analysis, familiarity with large-scale distributed computing, and a relevant technical degree or equivalent experience. Experience using cloud platforms like AWS, Azure, or Google Cloud, as well as tools such as Apache Hadoop or Spark, is highly valued. Strong problem-solving skills, attention to detail, and collaborative communication abilities help professionals excel in this position. These competencies are crucial for managing complex datasets, optimizing compute resources, and driving actionable insights within rapidly evolving data-driven environments.
What is a Data Crowd Compute job?
A Data Crowd Compute job involves distributing computational tasks across a large number of people or devices to process data efficiently. This type of work is often used in AI training, data annotation, or large-scale problem-solving. Workers contribute by performing small tasks that collectively build a larger solution. These jobs are common in machine learning, crowdsourcing, and distributed computing projects.
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Full-time
Posted 13 days ago
Key responsibilities
Define and drive full-stack enterprise AI factory baseline architectures across compute, networking, storage, virtualization, orchestration, security, observability, and NVIDIA AI software to deliver on-prem cloud native-platform and cluster reference builds.
Architect reference builds for end-to-end software systems and platforms, evaluate different platforms, capture information on implementation differences, and conduct research on platform behavior under different workloads.
Work with Product Management, Product Architects, Engineering, Solution Architecture, Program Management, and field teams to develop product direction, architecture requirements, roadmap inputs, and execution plans.
Job description
NVIDIA Enterprise Platforms Group is seeking a Senior System Architect to define, design, and validate enterprise AI factory reference architectures. This role sits at the intersection of product strategy, system architecture, customer requirements, and hands-on infrastructure validation, helping turn NVIDIA accelerated computing, networking, storage, and AI software into repeatable blueprints that enterprises and partners can deploy with confidence. The ideal candidate brings deep data center architecture experience, strong product and customer instincts, and practical proficiency across accelerated compute, high-performance networking, storage, Kubernetes, observability, automation, and AI/ML operations. This person can translate ambiguous customer and partner needs into clear requirements, architecture patterns, validation plans, and field-ready technical mentorship!
What you'll be doing:
Define and drive full-stack enterprise AI factory baseline architectures across compute, networking, storage, virtualization, orchestration, security, observability, and NVIDIA AI software to deliver on-prem cloud native-platform and cluster reference builds.
Architect reference builds for end-to-end software systems and platforms based on scalable, portable, and resilient builds and drive evaluation of different platforms, capture information on differences in implementations, and conduct research on the platform behavior under different workloads.
Work with Product Management, Product Architects, Engineering, Solution Architecture, Program Management, and field teams to develop product direction, architecture requirements, roadmap inputs, and execution plans
Develop and validate scalable cluster designs for enterprise AI/ML systems, including on-premises and hybrid-cloud deployments optimized for training, fine-tuning, inference, agentic AI, physical AI, and HPC workloads
Evaluate tradeoffs across performance, scalability, resiliency, manageability, security, power, cooling, cost, TCO, and operational complexity.
Understand design patterns, fundamental business logic, component-based architecture, and evolutionary architecture.
Build and detail comprehensive API strategies, middleware integrations, and orchestration workflows to ensure seamless communication across distributed enterprise software.
Integrate with non-cloud technologies and third-party vendor products/services.
What we need to see:
Bachelor's degree or equivalent experience.
12+ years of software or infrastructure architecture experience.
3+ years of experience with micro-services architectures.
Experience with system architecture, performance, and networking specifically developing and deploying distributed solutions.
Proven experience designing, building, or maintaining complex AI, HPC, or cloud-native infrastructure from rack-scale systems through full data center deployments.
Proven expertise in crafting and deploying complete software platforms spanning edge, on-premises, and cloud environments.
Strong understanding of GPU-accelerated systems, high-density servers, PCIe, NVLink, CPU/GPU platform design, rack integration, power, cooling, mechanical constraints, and data center deployment realities.
Deep networking knowledge across Ethernet, InfiniBand, RDMA, RoCE, routing, switching, congestion control, network segmentation, and high-performance cluster fabrics.
Deep proficiency in modern integration patterns, event-driven architectures (e.g., Kafka, RabbitMQ), and container orchestration (e.g., Kubernetes, Docker).
Strong grasp of cloud-native systems with emphasis on high availability, scalability, and security in compute environments.
Ways to stand out from the crowd:
Ability to work optimally with NVIDIA and its partners to deliver prescriptive, validated, and scalable enterprise AI factory architectures that reduce deployment complexity and accelerate time to value.
Ability to connect product vision, customer feedback, and deep system architecture to develop practical designs that enterprises can deploy, operate, and expand in production.
NVIDIA is widely considered one of the technology world's most desirable employers. We have some of the world's most forward-thinking and hardworking people on our team. If you're creative and autonomous, we want to hear from you!
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 208,000 USD - 327,750 USD for Level 5, and 240,000 USD - 379,500 USD for Level 6.You will also be eligible for equity and benefits.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive 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.
About Nvidia
Sourced by ZipRecruiter
NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.
Industry
Computer and electronic product manufacturing
Company size
10,000+ Employees
Headquarters location
Santa Clara, CA, US
Year founded
1993