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Embedded Ai Engineer Jobs in Quebec (NOW HIRING)

Norbert Health

Applied AI Engineer

Montreal, QC · On-site

The position We're looking for an Applied AI Engineer to take our growing collection of foundation ... Cutting-edge stack: embedded AI, robotics, LLMs, multimodal sensing * Transparent, mission-driven ...

Norbert Health

Applied AI Engineer

Montreal, QC

The position We're looking for an Applied AI Engineer to take our growing collection of foundation ... Cutting-edge stack: embedded AI, robotics, LLMs, multimodal sensing * Transparent, mission-driven ...

Bounteous

Applied AI Engineer

Montreal, QC · On-site

We are looking for senior, hands-on full-stack engineers who have designed, built, and operated ... Build AI-powered assistants embedded in Lending systems using agentic workflows. * Deliver ...

Norbert Health

Senior Backend Engineer

Montreal, QC · On-site

The Role We're looking for a Senior Backend Engineer to own and evolve the backbone of our system ... Cutting-edge stack: embedded AI, robotics, LLMs, multimodal sensing * Competing salaries and equity

Norbert Health

Signal Processing Engineer

Montreal, QC · On-site

The position We're looking for a Signal Processing Engineer to join our algorithm and development ... Cutting-edge stack: embedded AI, robotics, LLMs, multimodal sensing * Transparent, mission-driven ...

Norbert Health

Senior Backend Engineer

Montreal, QC

The Role We're looking for a Senior Backend Engineer to own and evolve the backbone of our system ... Cutting-edge stack: embedded AI, robotics, LLMs, multimodal sensing * Competing salaries and equity

Vention

Senior Embedded Developer

Montreal, QC · Hybrid

... software AI-powered platform built for the factory floor. Our technology powers over 25,000 ... As a Senior Embedded Developer at Vention... You'll own the technical layer that bridges hardware ...

Targeted Talent

Senior Deep Learning Engineer

Quebec, QC · On-site +1

$130K - $180K/yr

If you thrive on pushing the boundaries of AI technology, this role is for you! Requirements ... Experience in embedded or low-level programming * Knowledge of CUDA/OpenGL * Experience deploying ...

Targeted Talent

Senior Deep Learning Engineer

Montreal, QC · On-site +1

$130K - $180K/yr

If you thrive on pushing the boundaries of AI technology, this role is for you! Requirements ... Experience in embedded or low-level programming * Knowledge of CUDA/OpenGL * Experience deploying ...

Targeted Talent

Senior Deep Learning Engineer

Montreal, QC · On-site +1

$130K - $180K/yr

If you thrive on pushing the boundaries of AI technology, this role is for you! Requirements ... Experience in embedded or low-level programming * Knowledge of CUDA/OpenGL * Experience deploying ...

Targeted Talent

Senior Deep Learning Engineer

Quebec, QC · On-site +1

$130K - $180K/yr

If you thrive on pushing the boundaries of AI technology, this role is for you! Requirements ... Experience in embedded or low-level programming * Knowledge of CUDA/OpenGL * Experience deploying ...

KPMG

AI Builder- Senior Consultant

Montreal, QC

Embedded in business units (AI Builder - Internal): Supporting internal teams by building and ... engineering, business, strategy, design, and selftaught technical paths. This role is designed for ...

SB Quantum

Electrical Engineer

Sherbrooke, QC

By combining diamond-based quantum sensors with AI-driven algorithms, we transform complex magnetic ... Develop embedded firmware for microcontrollers, including system control logic, inter-component ...

SBQuantum

Electrical Engineer

Sherbrooke, QC · On-site

By combining diamond-based quantum sensors with AI-driven algorithms, we transform complex magnetic ... Develop embedded firmware for microcontrollers, including system control logic, inter-component ...

Levio

Senior Java Engineer

Montreal, QC · Hybrid

... embedded in our clients' environments. At Levio, we valueexpertise, curiosity, and continuous ... Hands-on experience with AI developer productivity tooling (e.g., GitHub Copilot, Amp, or similar)

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Showing results 1-20

All JobsEmbedded Ai Engineer JobsEmbedded Ai Engineer Jobs in Quebec

Embedded Ai Engineer information

What is an Embedded AI Engineer?

An Embedded AI Engineer is a professional who designs, develops, and implements artificial intelligence (AI) algorithms and models directly onto embedded systems, such as microcontrollers or edge devices. Their work involves optimizing AI solutions to run efficiently on hardware with limited computing resources, power, and memory. They collaborate with hardware engineers and software developers to integrate machine learning, computer vision, or other AI functionalities into products like smart appliances, autonomous vehicles, or IoT devices. Their expertise helps bring intelligent features directly to devices, enabling real-time decision-making without needing constant cloud connectivity.

What is the difference between Embedded Ai Engineer vs Machine Learning Engineer?

CriteriaEmbedded Ai EngineerMachine Learning Engineer
Required CredentialsBachelor's in Electrical Engineering, Computer Science, or related; knowledge of embedded systemsBachelor's or Master's in Computer Science, Data Science, or related; strong programming skills
Work EnvironmentEmbedded systems, IoT devices, hardware integrationData centers, cloud platforms, software development environments
Employer & Industry UsageConsumer electronics, automotive, IoT companiesTech firms, startups, research institutions
Common Search & ComparisonYesNo

Embedded Ai Engineers focus on integrating AI algorithms into embedded hardware and IoT devices, requiring knowledge of hardware constraints and embedded programming. Machine Learning Engineers develop models primarily for software applications and data analysis. While both roles involve AI, Embedded Ai Engineers specialize in hardware-software integration within embedded systems, whereas Machine Learning Engineers work on developing and deploying AI models in software environments.

What are the key skills and qualifications needed to thrive as an Embedded AI Engineer, and why are they important?

To thrive as an Embedded AI Engineer, you need expertise in embedded systems, AI/ML algorithms, programming languages like C/C++ and Python, and typically a degree in computer engineering or a related field. Familiarity with development tools such as TensorFlow Lite, ONNX, embedded Linux, and microcontroller platforms is essential, along with experience deploying AI models on resource-constrained devices. Strong problem-solving, collaboration, and communication skills help you work effectively in multidisciplinary teams and address real-world challenges. These skills ensure efficient integration of AI into embedded systems, enabling innovative, high-performance solutions for edge computing.

How does an Embedded AI Engineer typically collaborate with hardware and software teams during a project?

Embedded AI Engineers work closely with both hardware and software teams to ensure AI models are efficiently integrated into resource-constrained devices. They often collaborate with hardware engineers to optimize model performance based on device limitations like memory and processing power. At the same time, they coordinate with software developers to design efficient firmware and manage data pipelines. Regular cross-functional meetings and code reviews are common to address integration challenges and maintain alignment throughout the project lifecycle.
What are popular job titles related to Embedded Ai Engineer jobs in Quebec? For Embedded Ai Engineer jobs in Quebec, the most frequently searched job titles are:
What job categories do people searching Embedded Ai Engineer jobs in Quebec look for? The top searched job categories for Embedded Ai Engineer jobs in Quebec are:
Embedded Ai Engineer jobs near you
Infographic showing various Embedded Ai Engineer job openings in Quebec as of May 2026, with employment types broken down into 80% Full Time, and 20% Contract. Highlights an 60% In-person, 20% Hybrid, and 20% Remote job distribution.
Applied AI Engineer

Applied AI Engineer

Norbert Health

Montreal, QC • On-site

Full-time

Medical, Vision

Posted 11 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