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Nvidia

Developer Relations Manager, Higher Education and Research - Foundational AI

  • Seen live on Nvidia's site today
  • Senior
Pay
$170k to $220k a year CAD
Location
Canada, Toronto
Open for
18+ days
First seen
Oct 17, 2026
Apply on Nvidia's site (opens in a new tab)

Posting record

No flags

Open 18+ days

Nvidia's postings usually stay up 3 days

The posting's record, oldest first
  1. Nvidia's site dates the posting
  2. Nvidia's postings usually stay up 3 days; this one passes that
  3. Ghostless first sees this listing
  4. Last checked: still up
How we know

It hasn't been reposted, listed twice, or left up unusually long, and the posting doesn't say it's a talent pool.

Ghostless records the day it first sees a posting, so a repost can't reset its age. This one was already up when Ghostless started tracking Nvidia, so its true age is longer.

Last checked Nov 4, 2026.

How well do you match?

See how much of this posting your resume shows, and what it's missing.

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What it asks of you

8+ years of experience
“8+ years of experience” (quoted from the posting)
PhD asked for
“PhD in Computer Science, AI, Machine Learning, Applied Mathematics, Electrical Engineering, or a related technical field, or equivalent research d” (quoted from the posting)

What the posting discloses

Pay
$170k to $220k a year CAD
The base salary range is 170,000 CAD - 220,000 CAD for Level 4, and 225,000 CAD - 275,000 CAD for Level 5. (quoted from the posting)
Real vacancy
Yes, an existing vacancy
This posting is for an existing vacancy. (quoted from the posting)

Not stated: AI screening.

Why these three

Ontario requires postings from employers with 25 or more staff to state the pay, whether the vacancy exists, and whether AI screens applicants.

Skills mentioned

About the role

We are seeking a mission-driven Developer Relations Manager focused on Foundational AI Research to engage leading academic labs advancing the next generation of AI models, systems, and methods. In this role, you will work directly with top researchers building frontier AI systems, including large language models, multimodal models, reasoning systems, training methods, inference systems, model serving, and scalable AI infrastructure. You will help researchers adopt NVIDIA’s AI and accelerated computing platforms to push the boundaries of model performance, efficiency, and scale.

The ideal candidate brings deep technical credibility in foundational AI, strong research engagement experience, and ecosystem knowledge.

What you'll be doing

  • Serve as a trusted technical advisor to leading academic AI labs working on foundation models, LLMs, multimodal AI, reasoning, training, inference, and AI systems.
  • Identify high-impact research workloads where NVIDIA software, systems, and accelerated computing platforms can advance model performance, scale, and efficiency.
  • Engage principal investigators, postdocs, graduate researchers, and lab leadership to understand research goals, technical blockers, infrastructure needs, and collaboration opportunities.
  • Track frontier AI research across papers, benchmarks, open-source projects, and academic labs to identify emerging trends and future platform opportunities.
  • Partner with Research Account Managers, Solution Architects, Product, Engineering, and Business Development teams to support researcher adoption and long-term engagement.
  • Represent researcher needs internally by translating academic feedback into actionable insights for product roadmaps, developer programs, education, and platform strategy.
  • Support NVIDIA participation in major AI, ML, and systems research venues through technical content, workshops, university engagements, and lab-facing programs.

What we need to see

  • PhD in Computer Science, AI, Machine Learning, Applied Mathematics, Electrical Engineering, or a related technical field, or equivalent research depth.
  • 8+ years of experience
  • Deep expertise in foundational AI, including LLMs, multimodal models, generative AI, reasoning, post-training, model evaluation, or AI systems research.
  • Strong understanding of modern AI model development across the lifecycle, including pretraining, fine-tuning, post-training, optimization, evaluation, deployment, and model serving.
  • Hands-on experience with AI research stacks such as PyTorch, JAX, distributed training frameworks, inference systems, model serving platforms, evaluation pipelines, and GPU-accelerated workflows.
  • Technical fluency in scalable AI systems, including distributed training, parallelism strategies, checkpointing, memory optimization, batching, scheduling, latency, throughput, and cost-performance tradeoffs.
  • Familiarity with methods that improve model efficiency and performance, such as quantization, distillation, sparsity, speculative decoding, attention optimization, synthetic data generation, RLHF/RLAIF, and preference optimization.
  • Ability to engage top academic labs on frontier research challenges, including scaling behavior, compute efficiency, model quality, benchmark methodology, reproducibility, reliability, and research impact.
  • Demonstrated research credibility through publications, open-source contributions, academic collaborations, technical leadership, or direct work on frontier AI systems.

Ways to stand out from the crowd

  • Experience with NVIDIA AI platforms, including CUDA, CUDA-X libraries, TensorRT-LLM, Triton Inference Server, NIM, NeMo, Megatron, Transformer Engine, NCCL, DGX, NVLink, InfiniBand, or NVIDIA AI Enterprise.
  • Established relationships with leading AI labs, academic institutions, research institutes, benchmark communities, or major open-source AI projects.
  • Track record translating frontier AI research into demos, tutorials, reference architectures, workshops, technical blogs, or developer enablement programs.
  • Experience presenting at venues such as NeurIPS, ICML, ICLR, CVPR, AAAI , or related research workshops.
  • Ability to identify emerging research trends and convert them into strategic opportunities for collaboration, platform adoption, and ecosystem growth.

NVIDIA is widely considered to be one of the technology world’s most desirable employers! We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you. NVIDIA is committed to foster a diverse work environment and proud to be an equal opportunity employer!

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 170,000 CAD - 220,000 CAD for Level 4, and 225,000 CAD - 275,000 CAD for Level 5.

You will also be eligible for equity and benefits .

Applications for this job will be accepted at least until August 21, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

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