Forward Deployed Architect at NVIDIA

Santa Clara, California, United States

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Not SpecifiedCompensation

Expert & Leadership (9+ years)Experience Level

Full TimeJob Type

UnknownVisa

Technology, AIIndustries

Requirements

12+ years of experience in technical roles such as solutions architecture, ML engineering, technical product management, or technical consulting working across multiple customers or projects
Strong technical leadership with proven ability to guide teams and influence technical decisions without direct authority
Systems thinking with ability to understand customer business outcomes and translate them into effective technical approaches
Ability and willingness to prototype and help implement solutions hands-on keyboard when needed to solve critical problems or validate approaches
Exceptional communication skills with ability to engage technical teams, executives, and cross-functional stakeholders effectively
Bachelor's degree or equivalent experience
Ways to stand out (preferred)
Experience with NVIDIA Stack: CUDA, NeMo, Triton, TensorRT, NIM
Hands-on technical expertise in one or more of: AI/ML Systems (distributed training, large-scale inference, model optimization, pipeline automation); Infrastructure (Kubernetes, GPU scheduling, distributed computing frameworks like SLURM, Ray, multi-cloud environments); Observability & Automation (CI/CD, Infrastructure as Code, GPU performance monitoring)
Solutions architecture or consulting background with experience working across multiple customer engagements simultaneously
Technical pattern recognition with demonstrated ability to identify common challenges and develop reusable approaches

Responsibilities

Provide cross-account technical guidance: work across multiple strategic customer engagements to provide architectural direction, ensure alignment to business outcomes, and guide teams toward optimal technical approaches
Collaborate with customers and internal teams to grasp customer goals, significance, and effective technical strategies
Guide Forward Deployed Engineers and customer teams on complex technical decisions, system architectures, and implementation strategies to ensure successful outcomes
Identify common technical challenges, use cases, and solution approaches across projects; share findings with internal teams and the external community to improve AI implementation practices
Develop and advocate for standardized approaches, guidelines, and structured advice rooted in proven patterns from successful customer implementations
Dive into complex technical challenges hands-on when needed to solve critical problems, validate architectures, or demonstrate solutions
Collaborate closely with product, engineering, and customer success teams to ensure findings from customer engagements inform internal strategy and capabilities
Design technical strategies for sophisticated AI workloads including distributed training, inference optimization, and complex MLOps pipelines that can be applied across multiple customers

Skills

Key technologies and capabilities for this role

Solutions ArchitectureMachine LearningAI AcceleratorsDistributed TrainingInference OptimizationMLOpsSystem ArchitectureTechnical Leadership

Questions & Answers

Common questions about this position

What experience level is required for the Forward Deployed Architect role?

The role requires 12+ years of experience in technical roles such as solutions architecture, ML engineering, technical product management, or technical consulting working across multiple customers or projects.

What are the key skills needed for this position?

Key skills include strong technical leadership to guide teams without direct authority, systems thinking to translate business outcomes into technical approaches, hands-on prototyping ability, and exceptional communication skills with technical teams, executives, and stakeholders.

What education is required for this role?

A Bachelor's degree or equivalent experience is required.

Is this a remote position or does it require office work?

This information is not specified in the job description.

What is the salary or compensation for this role?

This information is not specified in the job description.

What skills will make me stand out as a candidate?

Experience with the NVIDIA stack including CUDA, NeMo, Triton, TensorRT, NIM, and hands-on expertise in AI/ML systems like distributed training, large-scale inference, model optimization, pipeline automation, or infrastructure such as Kubernetes, GPU scheduling, and distributed computing frameworks will help you stand out.

NVIDIA

Designs GPUs and AI computing solutions

About NVIDIA

NVIDIA designs and manufactures graphics processing units (GPUs) and system on a chip units (SoCs) for various markets, including gaming, professional visualization, data centers, and automotive. Their products include GPUs tailored for gaming and professional use, as well as platforms for artificial intelligence (AI) and high-performance computing (HPC) that cater to developers, data scientists, and IT administrators. NVIDIA generates revenue through the sale of hardware, software solutions, and cloud-based services, such as NVIDIA CloudXR and NGC, which enhance experiences in AI, machine learning, and computer vision. What sets NVIDIA apart from competitors is its strong focus on research and development, allowing it to maintain a leadership position in a competitive market. The company's goal is to drive innovation and provide advanced solutions that meet the needs of a diverse clientele, including gamers, researchers, and enterprises.

Santa Clara, CaliforniaHeadquarters

1993Year Founded

$19.5MTotal Funding

IPOCompany Stage

Automotive & Transportation, Enterprise Software, AI & Machine Learning, GamingIndustries

10,001+Employees

Benefits

Company Equity

401(k) Company Match

Risks

Increased competition from AI startups like xAI could challenge NVIDIA's market position.

Serve Robotics' expansion may divert resources from NVIDIA's core GPU and AI businesses.

Integration of VinBrain may pose challenges and distract from NVIDIA's primary operations.

Differentiation

NVIDIA leads in AI and HPC solutions with cutting-edge GPU technology.

The company excels in diverse markets, including gaming, data centers, and autonomous vehicles.

NVIDIA's cloud services, like CloudXR, offer scalable solutions for AI and machine learning.

Upsides

Acquisition of VinBrain enhances NVIDIA's AI capabilities in the healthcare sector.

Investment in Nebius Group boosts NVIDIA's AI infrastructure and cloud platform offerings.

Serve Robotics' expansion, backed by NVIDIA, highlights growth in autonomous delivery services.

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