Developer Relations Manager, AI Natives

Nvidia

Confirmed live yesterday High trust

Remote

Quick summary

Work type: Remote
Location: Remote
Salary: $152,000–$241,500 / yr
Posted: 43 days ago
Freshness: Confirmed live yesterday

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $215k

This role $197k

$139k most similar roles pay here $270k

This role pays less than 59% of similar roles. Most pay $175,668–$254,962 — the shaded band above. At the midpoint, this role pays about $197k versus about $215k 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 896 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 876 roles with salary data.

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At a glance

TL;DR · Developer Relations Manager, AI Natives

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Developer Relations Manager – AI Natives will serve as a technical advisor to AI-native companies building category-defining applications like developer copilots, agentic platforms, and multimodal creative tools. You will partner with founders and engineering teams to architect and optimize AI workloads using NVIDIA technologies including CUDA-X libraries, TensorRT-LLM, Triton Inference Server, NVIDIA NeMo, NIM microservices, and GPU-accelerated data processing frameworks. The role involves guiding startups through complex architectural decisions regarding model optimization, inference scaling, and real-time systems while collaborating with internal teams to influence the platform roadmap. You will develop reference architectures and best practices for scalable AI applications. Required expertise includes machine learning infrastructure, distributed systems, LLMs, and agent frameworks. Candidates should possess experience in software engineering or technical partnerships within high-growth developer ecosystems and large-scale inference infrastructure.

Skills

NVIDIA CUDA TensorRT-LLM Triton Inference Server NVIDIA NeMo NIM GPU Acceleration LLMs Agent Frameworks Multimodal AI Distributed Systems Machine Learning Infrastructure Model Optimization Inference Scaling RAPIDS

What you'll do

Serve as a technical advisor to AI-native companies building agentic systems, copilots, and multimodal tools.
Architect and optimize AI workloads using NVIDIA technologies like TensorRT-LLM, Triton Inference Server, and CUDA-X libraries.
Help startups scale training and inference infrastructure while optimizing for performance, cost efficiency, and latency.
Guide customers through complex architectural decisions regarding model optimization, agent frameworks, and real-time AI systems.
Influence the NVIDIA platform roadmap by identifying emerging AI categories with internal engineering and product teams.
Create reference architectures, AI blueprints, and best practices to help companies deploy scalable AI applications.
Build relationships with founders and technical leaders to establish NVIDIA as the preferred platform for innovative AI companies.
Partner with internal business development and solutions teams to accelerate the adoption of NVIDIA technologies.

What we're looking for

BS/MS degree in Computer Science, Engineering, or a related field is required or equivalent experience.
5+ years of experience in software engineering, developer relations, solutions architecture, technical partnerships, or product management.
Experience must be within AI, developer platforms, or large-scale software systems.
Hands-on experience building or scaling AI-powered products, developer platforms, or large-scale cloud services is required.
Expertise in machine learning infrastructure, model serving, distributed systems, and real-time AI applications is required.
Deep understanding of the modern AI stack including LLMs, agent frameworks, multimodal models, and inference optimization.
Proven ability to work with engineering teams and startup founders to influence product architecture and technical roadmaps.
Exceptional communication skills to explain complex AI systems to engineers, founders, and executives.

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