Used Tools & Technologies
Not specified
Required Skills & Competences ?
Docker @ 4 Kubernetes @ 4 Python @ 4 Machine Learning @ 4 MLOps @ 4 Data Science @ 4 LLM @ 4 PyTorch @ 4 CUDA @ 4 GPU @ 4Details
Are you a computational scientist, engineer, or data scientist passionate about working on the frontiers of artificial intelligence (AI) and high-performance computing (HPC)? NVIDIA is searching for a Solutions Architect to join our team in Canada and help customers solve challenging problems using AI. Solutions Architects are the primary technical contacts for our customers and engage deeply with scientific researchers and application developers. We need individuals who can develop positive relationships with researchers and developers, learn their requirements and work to bring solutions that enable their success. Your primary responsibilities will be to foster machine learning technical engagements with our largest Canadian enterprise customers.
Responsibilities
- Engage with AI developers and engineers across Canadian enterprise customers to understand goals, strategies, and technical needs and drive NVIDIA technology adoption in data center, edge, and cloud deployments.
- Facilitate AI use cases and proof-of-concepts on the NVIDIA platform.
- Collaborate with other solution architects, engineering, and product teams to understand technical needs and help define high-value solutions.
- Strategically support and partner with Canadian customers and industry-specific solution partners to help them adopt and build solutions using NVIDIA technology.
Requirements
- MS or PhD in Computer Science, Engineering, or a related field from an accredited university.
- 5+ years of relevant experience.
- Experience with modern AI software tools including PyTorch, JAX, TRT-LLM, vLLM, SGLang, or other frameworks.
- Programming experience with data science languages such as Python, and/or HPC languages such as C/C++/Fortran.
- Experience with GPUs and accelerated computing.
Ways to stand out
- Excellent knowledge of the theory and practice of deep learning, reinforcement learning, and/or large language models.
- CUDA/GPU optimization or CUDA-X library experience.
- Knowledge of MLOps technologies such as Docker/containers, Kubernetes, as well as cloud and data center deployments.
- Experience deploying large-scale GPU clusters.
- Experience deploying AI inference at scale on-premise or in the cloud.
Compensation & Benefits
- Base salary range (determined by location, experience, and internal pay rates):
- Level 3: 116,250 CAD - 201,500 CAD
- Level 4: 142,500 CAD - 247,000 CAD
- You will also be eligible for equity and benefits. More details are available on NVIDIA's benefits page.
Other details
- Location: Canada (Remote)
- Employment type: Full time
- Applications for this job will be accepted at least until July 29, 2025.
NVIDIA is an equal opportunity employer and provides reasonable accommodation for applicants with disabilities upon request.