Forward Deployed Architect at NVIDIA

Santa Clara, California, United States

NVIDIA Logo
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

Solutions Architecture
Machine Learning
AI Accelerators
Distributed Training
Inference Optimization
MLOps
System Architecture
Technical Leadership

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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