1

Ai Network Engineer Jobs in Quebec (NOW HIRING)

Support the AI Champions network and Communities of Practice * Contribute to measuring AI adoption ... Bachelor's degree in Information Technology, Software Engineering, Computer Science, or a related ...

New

Staff Frontend Engineer

Montreal, QC · On-site

CA$140K - CA$230K/yr

The goal: one unified network open to any person and any device, worldwide. Connection without ... Work on mission-critical projects, like our next-gen agentic AI chatbot that's redefining how ...

... AI infrastructure with a strong focus on reliability, performance, and cost-efficient design ... Deploy secure React and Python ML applications across AWS and Azure using private networking, MFA ...

Principal Backend Engineer

Montreal, QC · On-site

CA$160K - CA$220K/yr

The goal: one unified network open to any person and any device, worldwide. Connection without ... Experience integrating and leveraging AI-assisted development tools such as Claude and Opencode to ...

Implement gameplay systems from designer briefs: combat, abilities, movement, AI behaviours ... Implement multiplayer-safe gameplay code on engagements with networking requirements -- replication ...

Implement gameplay systems from designer briefs: combat, abilities, movement, AI behaviours ... Implement multiplayer-safe gameplay code on engagements with networking requirements - replication ...

Contribute to decisions with a tangible impact on parcel and freight transportation network ... For AI-related inquiries only, contact TalentCOE@purolator.com . To apply, visit our Careers Page.

Contribute to decisions with a tangible impact on parcel and freight transportation network ... For AI-related inquiries only, contact TalentCOE@purolator.com . To apply, visit our Careers Page.

Contribute to decisions with a tangible impact on parcel and freight transportation network ... For AI-related inquiries only, contact TalentCOE@purolator.com . To apply, visit our Careers Page.

Contribute to decisions with a tangible impact on parcel and freight transportation network ... For AI-related inquiries only, contact TalentCOE@purolator.com . To apply, visit our Careers Page.

Contribute to decisions with a tangible impact on parcel and freight transportation network ... For AI-related inquiries only, contact TalentCOE@purolator.com . To apply, visit our Careers Page.

Founded by Yoshua Bengio, LawZero is a nonprofit organization focused on AI safety. In charge of ... Design, deploy, and run Kubernetes clusters for research workloads, including autoscaling, network ...

AI for Reliability * Use AI for causal detection/anomalies to cut MTTR. * Develop reliability ... Networking and traffic: DNS, load balancers, CDN/edge, TLS/mTLS; fundamentals of BGP and global ...

That's why we equip our teams with cutting-edge technology, AI tools, and a collaborative ... Your mission will be to design, develop, and scale our network automation platform using cutting ...

Showing results 21-40

Ai Network Engineer information

What is an AI network engineer?

AI Network Engineers are professionals who design, implement, and maintain network infrastructures optimized for artificial intelligence (AI) applications. They ensure that networks can handle the high data throughput and low latency requirements of AI workloads, such as machine learning model training and inference. Their responsibilities may include integrating AI-driven network management tools, optimizing data flow for distributed AI systems, and ensuring data security and reliability. AI Network Engineers often collaborate with data scientists, AI researchers, and IT teams to deploy scalable and efficient AI solutions. As AI adoption grows, their role becomes increasingly important in supporting advanced technologies across industries.

What are the key skills and qualifications needed to thrive as an AI network engineer?

To thrive as an AI Network Engineer, you need expertise in computer networking, AI/ML concepts, and a strong background in computer science or a related field, often supported by a relevant degree or certifications like CCNP or AWS Certified Solutions Architect. Familiarity with network simulation tools, AI frameworks (such as TensorFlow or PyTorch), and network automation platforms is typically required. Problem-solving, analytical thinking, and effective communication are essential soft skills in this role. These skills are crucial for designing, deploying, and optimizing intelligent network systems that support scalable and efficient AI-driven solutions.

What are some common challenges AI network engineers face when deploying AI models at scale within enterprise networks?

AI Network Engineers often encounter challenges related to ensuring low-latency data transfer, handling large volumes of real-time data, and maintaining high security standards during AI model deployment. Integrating AI workloads with existing network infrastructure can require careful optimization of bandwidth and compute resources to prevent bottlenecks. Additionally, collaborating with data scientists and IT teams is essential for troubleshooting and refining deployment processes while keeping the network stable and scalable.
Infographic showing various Ai Network Engineer job openings in Quebec as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 11% Part Time, and 5% Contract. Highlights an 90% Physical, 3% Hybrid, and 7% Remote job distribution.

AI Hardware Validation Specialist (NVIDIA GPUs)

Montreal, QC • On-site

Other

Re-posted 25 days ago


Job description

About the Opportunity
Hello, I'm Charles Quinones, Recruitment Consultant at FED IT, specializing in permanent and contract recruitment within the Information Technology sector.
I'm currently recruiting for a well-established Canadian technology organization specializing in artificial intelligence infrastructure, high-performance computing (HPC), and advanced enterprise hardware solutions.
The company is looking for an AI Hardware Validation Specialist to join its engineering team and play a key role in validating next-generation AI computing platforms powered by NVIDIA technologies.

Mission

As part of the Engineering team, you will be responsible for validating, optimizing, troubleshooting, and supporting advanced AI-accelerated server platforms used in enterprise and high-performance computing environments.
Key responsibilities include:
Validate and test enterprise-grade AI hardware platforms featuring NVIDIA GPUs (H200, B200 and future generations);
Execute benchmarking, stress testing, and performance analysis to assess system stability and thermal efficiency;
Develop and execute comprehensive hardware validation plans;
Perform root cause analysis on GPU, memory, firmware, and system-level issues;
Optimize platform performance involving NVIDIA, AMD, and Intel technologies;
Support deployment and integration activities within laboratory and data center environments;
Validate air-cooled, direct liquid-cooled, and immersion-ready server solutions;
Install, maintain, and troubleshoot Linux-based systems;
Create automation scripts using Python and Bash for validation workflows;
Collaborate with engineering teams, technology vendors, and selected customers;
Produce detailed technical documentation and validation reports;
Stay current on emerging AI infrastructure and hardware technologies.

Your profile

Bachelor's degree in Computer Engineering, Electrical Engineering, Computer Science, or a related discipline;
5+ years of experience in hardware validation, systems integration, server engineering, or related fields;
Proven hands-on expertise with NVIDIA GPU technologies;
Strong familiarity with NVIDIA tools such as CUDA, NVML, and Nsight;
Advanced Linux administration and troubleshooting skills;
Strong understanding of server architecture, including CPUs, GPUs, memory, storage, and networking;
Experience scripting with Python and/or Bash;
Knowledge of AI infrastructure and HPC environments;
Exposure to immersion cooling or direct liquid cooling technologies is considered a strong asset;
Experience working for server manufacturers, system integrators, or OEM organizations is highly desirable.
Soft Skills
Strong analytical and problem-solving mindset;
Excellent troubleshooting and root-cause investigation skills;
Organized and detail-oriented documentation practices;
Ability to thrive in a fast-moving engineering environment;
Collaborative team player with a knowledge-sharing approach;
Self-starter who enjoys learning and tackling complex technical challenges.