ZipRecruiter

Log In

1

Ai Recruiting Jobs in Quebec (NOW HIRING)

previous pagenext page

Showing results 21-40

All JobsAi Recruiting JobsAi Recruiting Jobs in Quebec

Ai Recruiting information

What is the difference between Ai Recruiting vs Data Analyst?

AspectAi RecruitingData Analyst
Required CredentialsRecruitment certifications, HR experience, knowledge of AI toolsStatistics, data analysis, and visualization certifications or degrees
Work EnvironmentHR departments, recruitment agencies, tech companiesBusiness, finance, healthcare, and tech industries
Employer & Industry UsageUsed by HR teams to identify suitable candidates using AIUsed across industries to interpret data and generate insights
Search & Comparison IntentUnderstanding AI's role in recruitment processesAnalyzing data to inform business decisions

While both roles involve working with data and technology, Ai Recruiting focuses on leveraging AI tools to identify and attract candidates, often within HR and recruitment settings. Data Analysts interpret complex data sets to support decision-making across various industries. The two roles share skills in data handling but differ in their primary application and industry focus.

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

To thrive as an AI Recruiter, you need a strong understanding of recruitment processes, talent sourcing, and a working knowledge of AI and machine learning concepts, often supported by a background in HR or technical recruiting. Familiarity with applicant tracking systems (ATS), AI-driven sourcing tools, and data analytics platforms is typically required. Exceptional communication, relationship-building, and adaptability are crucial soft skills for engaging candidates and collaborating with hiring managers. These competencies are vital for efficiently identifying top tech talent and leveraging AI tools to optimize hiring outcomes.

How does an AI recruiting specialist typically collaborate with hiring managers and technical teams?

AI Recruiting specialists often serve as a bridge between hiring managers, technical teams, and candidates. They work closely with hiring managers to understand job requirements and use AI-driven tools to source and screen candidates efficiently. Regular meetings and feedback sessions help ensure that the candidates identified align with both the technical needs and the team culture. This collaborative process helps streamline hiring, reduce bias, and fill roles with top talent more quickly.

What is AI recruiting?

AI recruiting refers to the use of artificial intelligence technologies to automate and enhance various stages of the recruitment process. This includes tasks like screening resumes, scheduling interviews, sourcing candidates, and even predicting candidate suitability based on data analysis. AI recruiting tools help companies save time, reduce bias, and improve the overall hiring experience for both recruiters and applicants. These systems can analyze large amounts of data quickly, allowing recruiters to focus more on engaging with top talent.

How does AI recruiting work?

AI recruiting involves using artificial intelligence tools to automate and enhance the hiring process, including screening resumes, assessing candidate fit through algorithms, and scheduling interviews. Recruiters often utilize machine learning models and data analysis to identify the most suitable candidates efficiently and objectively.
Ai Recruiting jobs near you
Infographic showing various Ai Recruiting job openings in Quebec as of August 2026, with employment types broken down into 77% Full Time, 19% Part Time, 1% Temporary, and 3% Contract. Highlights an 70% Physical, 3% Hybrid, and 27% Remote job distribution.

AI Hardware Validation Specialist (NVIDIA GPUs)

Fed IT

Montreal, QC

Full-time

Posted 21 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.

Apply