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Ai Regulation Jobs in Quebec (NOW HIRING)

Apertera

Generative AI Engineer

Montreal, QC · On-site

Generative AI EngineerAbout Apertera Apertera is leading the evolution of language solutions for ... For more than twenty years, Apertera has set the bar for legal, financial, and regulatory ...

SIA

Generative AI Consultant

Montreal, QC

Application Development: Develop applications powered by GenAI models (both self-managed and API-accessible) that meet business needs and comply with applicable regulations (GDPR, EU AI Act, model ...

Jay Analytix

AI Engineer - Banking Domain

Montreal, QC · On-site

You will work across fraud detection, credit risk, regulatory compliance, and customer analytics, partnering with data, engineering, and compliance teams to bring AI from prototype to production. KEY ...

Jay Analytix

AI Engineer - Banking Domain

Montreal, QC · On-site

You will work across fraud detection, credit risk, regulatory compliance, and customer analytics, partnering with data, engineering, and compliance teams to bring AI from prototype to production. KEY ...

Norbert Health

Applied AI Engineer

Montreal, QC · On-site

... shipping under regulatory constraints. What you'll do * Integrate foundation models and ML ... Real-time voice AI pipelines (STT, TTS, streaming LLM) * Production RAG systems beyond toy ...

Norbert Health

Applied AI Engineer

Montreal, QC

... shipping under regulatory constraints. What you'll do * Integrate foundation models and ML ... Real-time voice AI pipelines (STT, TTS, streaming LLM) * Production RAG systems beyond toy ...

KPMG

Consultant - AI & Copilot

Montreal, QC · On-site

... regulations, servicing of English-speaking clients located across Canada and collaboration with ... AI Usage Weembrace the use of artificial intelligence (AI) to enhance the candidate experience and ...

Lassonde

Vice President, Data & Analytics

Quebec, QC · On-site

$140 - $200/hr

S. state privacy regimes, and the emerging AI regulatory landscape. * Oversee the ethical and responsible use of data and algorithms; ensure data used for financial and legal reporting is reliable ...

KPMG

Senior Consultant - AI & Copilot

Montreal, QC · On-site

... regulations, servicing of English-speaking clients located across Canada and collaboration with ... AI Usage Weembrace the use of artificial intelligence (AI) to enhance the candidate experience and ...

BRP

Solution Architect, AI

Montreal, QC · On-site

Ensure that all technology solutions comply with security, legal and regulatory requirements ... Understanding of industry use cases and AI adoption patterns (e.g., knowledge management ...

BRP

Solution Architect, AI

Montreal, QC · Hybrid

Ensure that all technology solutions comply with security, legal and regulatory requirements ... Understanding of industry use cases and AI adoption patterns (e.g., knowledge management ...

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All JobsAi Regulation JobsAi Regulation Jobs in Quebec

Ai Regulation information

Which 3 jobs will survive AI?

AI regulation professionals, data scientists, and cybersecurity specialists are likely to continue thriving as their roles involve overseeing AI systems, analyzing complex data, and protecting digital infrastructure. These jobs require specialized skills, critical thinking, and ongoing adaptation to technological changes, making them less susceptible to automation. Continuous learning and certification in relevant tools and frameworks help ensure job security in these fields.

Which jobs will resist AI?

Jobs that require complex human interaction, creativity, and emotional intelligence—such as healthcare providers, mental health professionals, skilled tradespeople, and certain education roles—are less susceptible to automation by AI. These roles often involve nuanced decision-making, hands-on skills, and empathy that AI cannot easily replicate. Additionally, jobs requiring physical presence in unpredictable environments are more resistant to AI automation.

What is the difference between Ai Regulation vs Data Privacy Officer?

AspectAi RegulationData Privacy Officer
Required CredentialsLegal or policy background, knowledge of AI systemsLegal, compliance, or privacy certifications (e.g., CIPP)
Work EnvironmentRegulatory agencies, tech companies, consulting firmsCorporate compliance departments, legal teams
Industry UsageAI development, tech regulation, policy makingData protection, privacy compliance, legal advisory

Ai Regulation professionals focus on creating and enforcing policies for AI systems, ensuring ethical and legal compliance. Data Privacy Officers primarily handle data protection policies, privacy laws, and safeguarding personal information. While both roles involve legal and compliance expertise, Ai Regulation emphasizes AI-specific policies, whereas Data Privacy Officers concentrate on data privacy laws and practices.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as a senior AI researcher, machine learning director, or AI executive, often requiring advanced skills in data science, programming, and AI frameworks. These roles usually involve leadership, strategic planning, and extensive experience, and they may be found in large tech companies or specialized AI firms.

What jobs can I get working with AI?

Jobs working with AI include roles such as AI engineer, machine learning engineer, data scientist, AI researcher, and AI product manager. These positions typically require skills in programming, data analysis, and understanding of AI algorithms, often involving tools like Python, TensorFlow, or PyTorch.
What are popular job titles related to Ai Regulation jobs in Quebec? For Ai Regulation jobs in Quebec, the most frequently searched job titles are:
What job categories do people searching Ai Regulation jobs in Quebec look for? The top searched job categories for Ai Regulation jobs in Quebec are:
Ai Regulation jobs near you
Infographic showing various Ai Regulation job openings in Quebec as of July 2026, with employment types broken down into 71% Full Time, 20% Part Time, and 9% Contract. Highlights an 63% Physical, 3% Hybrid, and 34% Remote job distribution.

Generative AI Engineer

Apertera

Montreal, QC • On-site

Full-time

Posted 3 days ago

Job description

Generative AI EngineerAbout Apertera

Apertera is leading the evolution of language solutions for high-stakes content. We partner with enterprises as an extension of their teams, combining professional expertise with Adaptive AI technology that is continuously refined by client context.

For more than twenty years, Apertera has set the bar for legal, financial, and regulatory translation, serving the most rigorous buyers, including over 75% of major national Canadian law firms, all major banks, and leading securities regulators.
Apertera is Canadian-owned, ISO 17100 and SOC 2 certified.

Our core values: 

  • Innovation
  • Dedication
  • Fanatical commitment to quality and service
  • Resourcefulness
  • Collaboration
About the Role

We are looking for a Generative AI Engineer to develop our next-generation intelligent translation and translation-related service engine, using Generative AI (GenAI) and Large Language Model (LLM) technologies. You will report to the team lead in AI Innovation, develop and implement state-of-the-art algorithms by fast prototyping, and collaborate with the software team to deploy models. We expect our Generative AI Engineer to to work at the intersection of LLM engineering, machine translation, cloud infrastructure, and evaluation. You'll play a pivotal role in pushing the boundaries of applying GenAI to translation scenarios and create innovative solutions.

Responsibilities
  • Implement state-of-the-art LLM techniques including continued pre-training, instruction fine-tuning, preference alignment, and LLM deployment.
  • Work closely with machine learning engineers and data engineers to design, build, and test models.
  • Develop efficient and scalable algorithms for training and inference of generative models, leveraging deep learning frameworks such as TensorFlow or PyTorch and optimizing performance on diverse hardware platforms.
  • Train and evaluate generative models using appropriate metrics and benchmarks, fine-tuning model parameters, architectures, and hyperparameters to optimize performance, stability, and generalization.
  • Built end-to-end prototypes that are production ready.
  • Work closely with software and DevOps engineers to deploy GenAI models.    
  • Document code, algorithms, and experimental results, following best practices for reproducibility, version control, and software engineering, and contributing to internal knowledge sharing and continuous improvement initiatives.
Requirements
  • Bachelor's degree in Computer Science, Artificial Intelligence, Machine Learning, or related fields. A Master’s degree is preferred.
  • 2+ years of industry experience developing GenAI and LLM applications is preferred.
  • Proficiency in Python programming and software development practices, with experience in building and maintaining scalable, production-grade software systems.
  • Working knowledge and project-based record of all of the following: context engineering, RAG, harness engineering.
  • Working knowledge and project-based record of at least one of the following is a plus: LLM post-training, APO, agentic workflow.
  • Strong problem-solving skills, attention to detail, and the ability to work independently and collaboratively in a fast-paced environment.
  • Hands-on experience with Huggingface APIs or Amazon Bedrock. 
  • Expert skills of Python, including PyTorch, TensorFlow, Pandas, etc.
  • Experience with cloud platforms like AWS, GCP, or Azure 
  • Excellent problem-solving skills, critical thinking, and the ability to work independently and collaboratively in a fast-paced environment.
  • Strong communication skills, with the ability to articulate complex technical concepts effectively and work cross-functionally with diverse teams.
  • Self-driven, self-motivated with excellent time management skills
  • Excellent organizational, communication, and interpersonal skills
  • Ability to adapt to shifting priorities without compromising deadlines and momentum.

 

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