Senior Forward Deployed Engineer, Open Models

Nvidia

Confirmed live today High trust

Quick summary

Work type
On-site
Location
Santa Clara, CA
Salary
$184,000–$287,500 / yr
Employment
Full-time
Posted
9 days ago
Freshness
Confirmed live today

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $188k
This role $236k
$136k $304k
below market most similar roles pay here above market

This role pays more than 86% of similar roles. Most pay $153,684–$222,625 — the blue band above. At the midpoint, this role pays about $236k versus about $188k for comparable roles.

Based on 240 similar postings.

Employer

About Nvidia

Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing

Nvidia currently has 1623 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 1110 roles with salary data.

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At a glance

TL;DR · Senior Forward Deployed Engineer, Open Models

The Senior Forward Deployed Engineer joins the team to drive technical engagement with partners and customers across the open model portfolio, including NVIDIA Nemotron and NVIDIA Cosmos. This role involves turning open models into production-ready AI by leading technical engagements from discovery through post-training and harness optimization. Day-to-day responsibilities include building synthetic data pipelines, designing evaluations, and performing supervised fine-tuning, reinforcement learning, and LoRA. The engineer will also optimize inference for cost-effectiveness and create reusable recipes and playbooks for the ecosystem. Required skills include proficiency in PyTorch, Hugging Face Transformers, Python, and Linux, alongside expertise in large-scale distributed training and multi-GPU systems. The work focuses on unlocking the post-trainability and inference cost-effectiveness of open models for specific domain applications.

What does a Forward Deployed Engineer earn?

Median $219575 from 46 postings across 19 companies.

See salary data

What you'll do

  • Drive AI solutions from initial discovery and scoping through post-training, harness optimization, and production deployment.
  • Design and build synthetic data pipelines, dataset curation, and evaluation sets for domain-specific models.
  • Execute post-training methods including LoRA, supervised fine-tuning, and synchronous/asynchronous reinforcement learning.
  • Tune model harnesses for prompting, tool use, orchestration, and context management to improve domain performance.
  • Optimize inference performance for cost-effective production deployment across multi-GPU and multi-node systems.
  • Lead technical engagements by scoping work, shaping statements of work, and driving delivery with partner engineering teams.
  • Create reusable recipes, reference pipelines, and playbooks to enable partners to scale independently.
  • Translate field insights from customer engagements back into NVIDIA's product, research, and software stack.

What we're looking for

  • Bachelor's, Master's, or PhD in Computer Science, Engineering, Machine Learning, or a related field, or equivalent experience.
  • 8+ years in ML or software engineering, applied AI, FDE, or solutions architecture.
  • 3–5+ years of hands-on LLM post-training and taking models to production.
  • Solid fundamentals in deep learning and machine learning.
  • Deep expertise in post-training methods including LoRA/PEFT, SFT, and reinforcement learning.
  • Good understanding of large-scale distributed training and inference performance optimization.
  • Proficiency in PyTorch, Hugging Face Transformers, Python, and Linux.
  • Proven ability to scope engagements, shape SOWs, and lead delivery with partners and customers.

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