Forward Deployed Engineer, AI Accelerator

at Nvidia
📍 Santa Clara, United States
USD 168,000-322,000 per year
MIDDLE SENIOR
✅ Hybrid

SCRAPED

Used Tools & Technologies

Not specified

Required Skills & Competences ?

Ansible @ 3 Docker @ 3 Kubernetes @ 3 Linux @ 6 DevOps @ 6 Terraform @ 3 Python @ 3 GCP @ 3 CI/CD @ 3 Distributed Systems @ 3 MLOps @ 3 TensorFlow @ 3 AWS @ 3 Azure @ 3 ServiceNow @ 3 API @ 3 PyTorch @ 3 Salesforce @ 3 CUDA @ 3 GPU @ 3

Details

NVIDIA is seeking a Forward Deployed Engineer to join the AI Accelerator team, working directly with strategic customers to implement and optimize pioneering AI workloads. You will provide hands-on technical support for advanced AI implementations and complex distributed systems, ensuring customers achieve optimal performance from NVIDIA's AI platform across diverse environments. The role works directly with leading AI companies to solve difficult technical challenges.

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 GPU scheduling systems.
  • 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.

Requirements

  • 8+ years of experience in customer-facing technical roles (Solutions Engineering, DevOps, ML Infrastructure Engineering) or equivalent.
  • BS, MS, or Ph.D. in Computer Science, Computer Engineering, Electrical Engineering, or a related technical field, or equivalent experience.
  • Strong proficiency with Linux systems.
  • Experience with distributed computing and large-scale AI/ML workloads (training and inference).
  • Experience with Kubernetes, containerization (Docker), and GPU scheduling systems.
  • Programming skills in Python and experience with AI frameworks such as PyTorch or TensorFlow.
  • Ability to engage with customers and work effectively with technical teams under high-pressure situations.

Ways to stand out (Preferred / Nice to have)

  • Experience with NVIDIA ecosystem: DGX systems, CUDA, NeMo, Triton, or NIM.
  • Hands-on experience with cloud AI services (AWS, Azure, GCP).
  • MLOps expertise including CI/CD pipelines, container orchestration, and observability tooling.
  • Infrastructure-as-code experience (Terraform, Ansible) and automation for deployments.
  • Enterprise software integration experience (Salesforce, ServiceNow) for customer environments.

Compensation & Benefits

  • Base salary range by level (location- and experience-dependent):
    • Level 4: 168,000 USD - 264,500 USD per year
    • Level 5: 200,000 USD - 322,000 USD per year
  • Eligible for equity and NVIDIA benefits (link to benefits provided in original posting).

Additional information

  • Employment type: Full time.
  • Location: Santa Clara, CA, United States. Role tagged as #LI-Hybrid.
  • Applications accepted at least until September 6, 2025.
  • NVIDIA is an equal opportunity employer committed to fostering a diverse work environment.