Forward Deployed Engineer, AI Accelerator at NVIDIA

Santa Clara, California, United States

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Artificial Intelligence, TechnologyIndustries

Requirements

8+ years of experience in customer-facing technical roles (Solutions Engineering, DevOps, ML Infrastructure Engineering)
BS, MS, or Ph.D. in CS, CE, EE (related technical field) or equivalent experience
Strong proficiency with Linux systems, distributed computing, Kubernetes, and GPU scheduling
AI/ML experience supporting inference workloads and training at large-scale
Programming skills in Python, with experience in PyTorch, TensorFlow, or similar AI frameworks
Customer engagement ability to work effectively with technical teams under high-pressure situations

Responsibilities

Design and deploy custom AI solutions including distributed training, inference optimization, and MLOps pipelines across customer environments
Provide remote technical support to strategic customers, optimize AI workloads, diagnose and resolve performance issues, and guide technical implementations through virtual collaboration
Deploy and manage AI workloads across DGX Cloud, customer data centers, and CSP environments using Kubernetes, Docker, and scheduling systems for GPU
Profile and optimize large-scale model training and inference workloads, implement monitoring solutions, and resolve scaling challenges
Build custom integrations with customer systems, develop APIs and data pipelines, and implement enterprise software connections
Create implementation guides, documentation for resolution approaches and standard methodologies for complex AI deployments

Skills

Key technologies and capabilities for this role

KubernetesDockerMLOpsDistributed TrainingInference OptimizationGPUAPIsData PipelinesProfilingMonitoring

Questions & Answers

Common questions about this position

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

The role requires 8+ years of experience in customer-facing technical roles such as Solutions Engineering, DevOps, or ML Infrastructure Engineering.

What are the key technical skills needed for this position?

Candidates need strong proficiency with Linux systems, distributed computing, Kubernetes, and GPU scheduling, along with AI/ML experience in inference workloads and training at large-scale, and programming skills in Python with PyTorch, TensorFlow, or similar frameworks.

Is this a remote position or does it require on-site work?

The role involves providing remote technical support to strategic customers through virtual collaboration, though it may include work across customer data centers and cloud environments.

What is the salary or compensation for this role?

This information is not specified in the job description.

What makes a candidate stand out for this Forward Deployed Engineer position?

Experience with the NVIDIA ecosystem like DGX systems, CUDA, NeMo, Triton, or NIM, cloud platforms such as AWS, Azure, or GCP AI services, MLOps expertise, infrastructure as code tools like Terraform or Ansible, and enterprise software integrations 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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