Senior AI Engineer (NVIDIA + LLM Inference) - Onsite - Toronto, Canada
- Toronto, ON, Canada
Full-time
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Job details
- Job type
- Full-time
- Apply by
- Experience
- 5+ years of professional experience in AI/ML engineering, software engineering, or machine learning infrastructure.
- Posting language
- English
- Posted
Original job description
About FullStack
FullStack is your AI-native engineering partner, built to turn AI capability into certainty. Most companies can demo AI; few can get it to production and prove what it produced. We close that gap with three capabilities, AI built into your products from the start, elite vetted talent who apply it, and transparent execution that shows value every step of the way. With now over 600 customers in North America, FullStack is one integrated partner for all your AI engineering needs. With FullStack, you move forward with confidence.
We’re Most Proud Of
Join our talent network and connect with U.S. clients for flexible, project-based development work as a Senior AI Engineer (NVIDIA + LLM Inference).
We’re Seeking Engineers Who Are AI-enthusiastic In Their Workflow. Professional Experience Or Personal Project Work With The Following Is a Significant Plus
Learn more about our Applicants Privacy Notice.
FullStack is your AI-native engineering partner, built to turn AI capability into certainty. Most companies can demo AI; few can get it to production and prove what it produced. We close that gap with three capabilities, AI built into your products from the start, elite vetted talent who apply it, and transparent execution that shows value every step of the way. With now over 600 customers in North America, FullStack is one integrated partner for all your AI engineering needs. With FullStack, you move forward with confidence.
We’re Most Proud Of
- Offering life-changing career opportunities to talented software professionals across the Americas.
- Building highly-skilled software development teams for hundreds of the world’s greatest companies.
- Having delivered hundreds of successful custom software solutions, which have positively impacted the lives and careers of millions of users.
- Our 4.1-star rating on GlassDoor.
- Our client Net Promoter Score of 68, twice the industry average.
Join our talent network and connect with U.S. clients for flexible, project-based development work as a Senior AI Engineer (NVIDIA + LLM Inference).
- You will integrate directly into our client's team and work alongside their existing designers and engineers on a daily basis.
- 5+ years of professional experience in AI/ML engineering, software engineering, or machine learning infrastructure.
- Advanced English is required.
- Successful completion of a four-year college degree is required.
- Strong hands-on experience with NVIDIA's AI inference stack, particularly NVIDIA NIM, NeMo, NeMo Guardrails, TensorRT-LLM, and Triton Inference Server.
- Proven experience deploying and self-hosting LLMs and embedding models in production on GPU infrastructure.
- Practical experience serving and scaling inference workloads, including GPU cluster operations and Kubernetes-based environments, ideally using the NVIDIA GPU Operator.
- Strong theoretical and applied understanding of LLMs, including inference optimization, model serving, and the operational challenges of running models at scale.
- Experience building and operating private, on-premises AI inference platforms in secure environments.
- Ability to implement guardrails and controls for production LLM applications.
- Experience working in banking or other regulated industries is a plus.
- Ability to work through new and difficult issues and contribute to libraries as needed.
- Ability to create and maintain continuous integration and delivery of applications.
- Forensic attention to detail.
- A positive mindset and a can-do attitude.
- Experience working on Agile / Scrum teams.
- Meaningful experience working on large, complex systems.
- Ability to take extreme ownership over your work. Every day is a challenge to ensure you are performing to the expectations you and your team have agreed upon.
- Ability to identify with the goals of FullStack's clients, and dedicate yourself to delivering on the commitments you and your team make to them.
We’re Seeking Engineers Who Are AI-enthusiastic In Their Workflow. Professional Experience Or Personal Project Work With The Following Is a Significant Plus
- Cursor, Windsurf, or Google Antigravity.
- Claude Code, Gemini CLI, Codex, or Copilot CLI.
- Applicants must be currently authorized to work in the country of this job posting on a full-time basis.
- FullStack will not sponsor applicants for work visas now or in the future.
- Competitive pay.
- The ability to work with leading startups and Fortune 500 companies.
- Continuing education opportunities.
- Opportunity to grow and expand your career.
Learn more about our Applicants Privacy Notice.
More about this job
Responsibilities
Deploy, self-host, serve, and scale LLMs and embedding models in production on GPU infrastructure, including Kubernetes-based clusters and secure, on-premises platforms. Build and operate inference systems with optimization, model-serving controls, and guardrails for production LLM applications.
Requirements
Requires at least five years of relevant AI/ML engineering, software engineering, or machine learning infrastructure experience, advanced English, and a completed four-year college degree. Candidates should have hands-on experience with NVIDIA inference technologies, production GPU workloads, Kubernetes, LLM operations, and CI/CD; regulated-industry experience is a plus.
Skills
- NVIDIA AI Inference Stack
- NVIDIA NIM
- NeMo
- NeMo Guardrails
- TensorRT-LLM
- Triton Inference Server
- LLM Deployment
- Embedding Models
- GPU Infrastructure
- Kubernetes
- GPU Cluster Operations
- Inference Optimization
- Model Serving
- On-Premises AI Platforms
- Continuous Integration and Delivery
- Agile/Scrum
Benefits
- Competitive Pay
- Continuing Education Opportunities
- Career Growth Opportunities
Visa sponsorship
Not detected in the job text
Categories
- Technology
- Software
- Engineering
- Data & Analytics
- Security & Safety
Keywords
- Artificial Intelligence
- Machine Learning
- NVIDIA
- NVIDIA NIM
- NeMo
- NeMo Guardrails
- TensorRT-LLM
- Triton Inference Server
- Large Language Models
- Embedding Models
- LLM Inference
- GPU Infrastructure
- GPU Clusters
- Kubernetes
- NVIDIA GPU Operator
- Inference Optimization
- Model Serving
- On-Premises AI
- Secure Environments
- Guardrails
- Production Deployment
- Machine Learning Infrastructure
- Continuous Integration
- Continuous Delivery
- Agile
- Scrum
- Banking
- Regulated Industries
- Cursor
- Windsurf