Developer Relations Manager, Higher Education and Research - Foundational AI
- Toronto, ON
- On-site
- Posted Aug 17, 2026
- 1 position
$170,000–$275,000 / year
Opens an external site
- Employment type
- Full-time
- Experience level
- Senior · 8+ years
- Minimum education
- Master’s degree
- Posting language
- English
- Working hours
- 40 hours per week
Job summary
You will serve as a technical advisor to academic AI labs, identifying high-impact research workloads and facilitating the adoption of NVIDIA's accelerated computing platforms. Additionally, you will partner with internal engineering and product teams to translate academic feedback into actionable insights for platform strategy and roadmaps.
Job details
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.
What you’ll do
You will serve as a technical advisor to academic AI labs, identifying high-impact research workloads and facilitating the adoption of NVIDIA's accelerated computing platforms. Additionally, you will partner with internal engineering and product teams to translate academic feedback into actionable insights for platform strategy and roadmaps.
Requirements
Candidates must hold a PhD in a technical field such as Computer Science or AI, with at least 8 years of relevant experience. You must possess deep expertise in foundational AI model development, scalable AI systems, and hands-on experience with research stacks like PyTorch and JAX.
Benefits
- Equity
- Health benefits
Listed skills
- Évaluation · Preferred
- Technical · Preferred
- Training · Preferred
- Collaboration · Preferred
- Leadership · Preferred
- Health · Preferred
- Teams · Preferred
- Development · Preferred
- future · Preferred
- efficiency · Preferred
- Hardworking · Preferred
- Business development · Preferred
Other relevant skills
Identified from the job description. Confirm important requirements above.
- Foundational AI
- Large Language Models
- Multimodal Models
- PyTorch
- JAX
- Distributed Training
- Inference Systems
- Model Serving
- GPU-accelerated Workflows
- CUDA
- TensorRT-LLM
- Triton Inference Server
- Technical Advisory
- Research Engagement
- Scalable AI Infrastructure
- Generative AI
- Large Language Modeling
- Transformer (Machine Learning Model)
- Pipelines
- Synthetic Data Generation
- Generative Artificial Intelligence
- Product Roadmaps
- Distributed Machine Learning
- Workflow Management
- AI Research
- Technical Leadership
- Research
- Artificial Intelligence
- Computing Platforms
- Electrical Engineering
- Applied Mathematics
- Business Development
- Program Optimization
- Collaborative Software
- Computer Science
- Nvidia CUDA
- Tutorials
- Systems Theories
- Leadership
- Scalability
- InfiniBand
- Machine Learning
- Reasoning Systems
- Product Engineering
- Software Systems
- Solution Architecture
- Scheduling
- Quantization
- Blogs
- PyTorch (Machine Learning Library)
Job areas
- Technology
- Science & Research
- Software
- Engineering
- Education
- Developer Relations Manager
- Software Development / Engineering Manager
- Software Developers
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