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Ai Rating Jobs in Quebec (NOW HIRING)

Norbert Health

Applied AI Engineer

Montreal, QC · On-site

  • Medical

  • Vision

... rate, more in the pipeline), running assessments, documenting to the EMR, and escalating when something's wrong. Autonomously. We're not building demos. We're deployed in real facilities today ...

Norbert Health

Applied AI Engineer

Montreal, QC · On-site

  • Medical

  • Vision

... rate, more in the pipeline), running assessments, documenting to the EMR, and escalating when something's wrong. Autonomously. We're not building demos. We're deployed in real facilities today ...

Desjardins Group

Senior Advisor, AI Model Risk

Montreal, QC · Hybrid

  • Medical

  • Retirement

  • PTO

The AI Risk Management and Governance team oversees the development, deployment and use of ... Challenge risk ratings and proposed mitigation measures * Contribute to the implementation of model ...

Acara Solutions

... AI-generated calls, text messages, or emails from Acara Solutions and its affiliates, and contracted partners. Frequency varies for text messages. Message and data rates may apply. Carriers are not ...

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Ai Rating information

What is an AI rater?

An AI Rating job involves evaluating artificial intelligence systems, models, or algorithms based on specific criteria such as accuracy, fairness, and performance. Professionals in this role assess AI-generated content, provide feedback, and help improve machine learning models. They may work on tasks like rating search engine results, analyzing chatbots, or reviewing AI-generated text and images. This role is critical in training AI systems to be more reliable and user-friendly.

What does an AI rater do?

As an AI Rater, your primary responsibility is to evaluate search results, advertisements, or other AI-generated content for relevance, accuracy, and quality according to provided guidelines. You may spend your workdays reviewing data sets, rating outputs, and providing feedback to help optimize machine learning algorithms. The role often involves independent, remote work while following clear evaluation standards and meeting productivity goals. Consistent attention to detail and impartiality are crucial to ensure your assessments help enhance the overall AI system performance.

What skills and qualifications are needed to thrive as an AI rater?

To excel as an AI Rater, you need strong analytical skills, attention to detail, and familiarity with computer-based evaluation, often supported by a relevant educational background or work experience in data annotation or quality assessment. Experience using web-based evaluation platforms, and sometimes basic knowledge of machine learning frameworks, is valuable. Critical thinking, adaptability, and clear written communication are important soft skills for providing precise and actionable feedback. These abilities ensure that AI systems are accurately assessed and improved, directly impacting the quality and effectiveness of AI-driven products.

What are popular job titles related to Ai Rating jobs in Quebec?

For Ai Rating jobs in Quebec, the most frequently searched job titles are:

What job categories do people searching Ai Rating jobs in Quebec look for?

The top searched job categories for Ai Rating jobs in Quebec are:

Ai Rating jobs near you
Infographic showing various Ai Rating job openings in Quebec as of August 2026, with employment types broken down into 78% Full Time, 19% Part Time, and 3% Contract. Highlights an 68% Physical, 4% Hybrid, and 28% Remote job distribution.

Applied AI Engineer

Norbert Health

Montreal, QC • On-site

Full-time

Medical, Vision

Re-posted 23 days ago

Job description

The company

Norbert is building autonomous robots that deliver healthcare.

Our AI sensing platform enables existing robotic platforms to become care team members: rounding on patients, capturing vitals without contact (FDA-cleared for pulse and respiratory rate, more in the pipeline), running assessments, documenting to the EMR, and escalating when something's wrong. Autonomously.

We're not building demos. We're deployed in real facilities today, monitoring hundreds of patients daily. We're solving one of healthcare's hardest problems: a global nursing shortage that will hit 40% by 2030.

We're a small, international team backed by top-tier VCs, with offices in Brooklyn, Paris, and Montreal. We ship things that matter.

The position

We're looking for an Applied AI Engineer to take our growing collection of foundation models and ML components from manually run, sometimes locally trained workflows to fully automated, production-grade MLOps pipelines: deployed reliably on robots in nursing facilities. We need someone who knows the model landscape cold, treats evaluation as a first-class engineering problem, and has strong opinions about when to prompt, RAG, fine-tune, swap, or buy.

You'll work across cloud and edge deployments, and some of the systems you'll touch are on a SaMD pathway, so you'll need to be comfortable shipping under regulatory constraints.

What you'll do
  • Integrate foundation models and ML components (VLMs, LLMs, ASR/TTS, detection/segmentation, embeddings) into our production pipelines, using both open-weight models and third-party APIs
  • Build RAG and agent-style orchestration for clinical reporting and conversational interfaces
  • Ship real-time streaming pipelines (voice agents) alongside batch and request-response workloads
  • Build evaluation harnesses that catch regressions across model swaps and measure performance against clinical-grade accuracy targets
  • Fine-tune and retrain models (LoRA, PEFT, supervised fine-tuning) using data collected from our deployed fleet
  • Deploy across our inference surfaces: third-party APIs, self-hosted, and on-robot edge
  • Build the data flywheel: pipelines that collect, label, version, and feed production data back into model improvement
  • Partner with the algorithms team (signal processing, computer vision) on integration with their lower-level pipelines
What we're looking for
  • BS in Computer Science, Engineering, or a related field, or equivalent hands-on experience
  • 4+ years shipping ML/AI systems in production outside of academic settings
  • Strong working knowledge of the modern foundation model landscape (open-weight LLMs and VLMs, common detection/segmentation backbones, embedding models)
  • Hands-on experience with PEFT/LoRA and supervised fine-tuning
  • Strong Python; comfortable with the deployment toolchain (ONNX, quantization, at least one inference runtimeTensorRT, vLLM, llama.cpp, etc.)
  • Experience with a cloud ML training/MLOps platform (GCP Vertex AI, AWS SageMaker, Azure ML, or equivalent)
  • Ability to work independently, solve complex problems, and drive projects to completion
Bonus points
  • Edge ML deployment (Jetson, ARM, mobile NPUs)
  • Real-time voice AI pipelines (STT, TTS, streaming LLM)
  • Production RAG systems beyond toy implementations
  • Medical devices, SaMD, or other regulated ML environments
  • MLOps tooling (Weights & Biases, MLflow, DVC, etc.)
  • Active learning or human-in-the-loop labeling workflows
  • C++ for integrating with our computer vision pipeline
What we offer
  • Real impact: your code provides care for patients today
  • High autonomy and technical ownershipyou'll define how we operate AI in production
  • Work at the intersection of cutting-edge AI, edge computing, and healthcare
  • A talented, excellent, diverse and international team
  • Equity participation in the company's future
  • Cutting-edge stack: embedded AI, robotics, LLMs, multimodal sensing
  • Transparent, mission-driven culture focused on continuous learning
  • Competitive salary and equity