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Embedded Machine Learning Engineer Jobs in Winnipeg, MB

... embedded analytics, operational workflows, machine learning, and emerging AI use cases. * Build ... Partner with product, software engineering, analytics, and AI stakeholders to translate business ...

Our solutions help the world's biggest brands leverage artificial intelligence, machine learning ... As Senior Cloud Engineer, you'll be a senior individual contributor focused on building secure ...

Our solutions help the world's biggest brands leverage artificial intelligence, machine learning ... As Senior Software Developer, You Will... * Work with a team of developers to build AI Driven ...

Tasks involve optimizing machine performance, ensuring program accuracy and efficiency, and ... On-the-job training in a continuous learning environment (we've invested 10.9 million in 2023)

Our solutions help the world's biggest brands leverage artificial intelligence, machine learning ... You'll work closely with Technical Solutions, Product, and Engineering to solve difficult problems ...

Our solutions help the world's biggest brands leverage artificial intelligence, machine learning ... You'll work directly with customers and across Customer Success, Product, Engineering ...

Field Service Engineer

Winnipeg, MB ยท On-site

CA$35 - CA$45/hr

Whether lasers, machine tools, EUV or electronics - TRUMPF is building technological worlds for ... Do you enjoy travel, learning about new places, and meeting new people? Are you interested in ...

Coordinate and liaise with supply, sales, engineering and customer service to ensure production ... Previous machine shop, manufacturing, aerospace, or MRO experience is considered an asset.

Do you enjoy working with tools and seeing a machine come together piece by piece? We want to hear ... A hands-on entry point into the mining and engineering world, working on world-class underground ...

Maintenance Technician

Landmark, MB ยท On-site

CA$23/hr

Scheduling, tracking, and completing preventative maintenance on all machinery and boilers ... Learning and development opportunities to support your career path. * Inclusive and values-driven ...

Embedded Machine Learning Engineer information

See Winnipeg, MB salary details

$26.6K

$142.2K

$229.3K

How much do embedded machine learning engineer jobs pay per year?

As of Sep 3, 2026, the average yearly pay for embedded machine learning engineer in Winnipeg, MB is $142,152.00, according to ZipRecruiter salary data. Most workers in this role earn between $107,503.00 and $175,077.00 per year, depending on experience, location, and employer.

What does an embedded machine learning engineer do?

An Embedded Machine Learning Engineer designs and implements machine learning models that can run efficiently on embedded systems, such as microcontrollers and edge devices. Their work involves optimizing algorithms to fit within the resource constraints of these devices, integrating ML models into hardware, and ensuring real-time performance. They collaborate closely with hardware engineers and software developers to deploy intelligent features in products like smart sensors, IoT devices, and autonomous systems.

What are the key skills and qualifications needed to thrive as an embedded machine learning engineer?

To thrive as an Embedded Machine Learning Engineer, you need expertise in machine learning algorithms, embedded systems programming (C/C++ or Python), and a solid understanding of hardware constraints, usually supported by a degree in computer science, electrical engineering, or related fields. Familiarity with tools like TensorFlow Lite, ONNX, microcontroller SDKs, and experience with real-time operating systems (RTOS) are typically required. Strong problem-solving, communication skills, and the ability to collaborate across multidisciplinary teams help you stand out in this role. These skills are crucial for efficiently deploying intelligent models on resource-constrained devices, ensuring optimal performance and seamless integration in real-world applications.

What are some common challenges faced by embedded machine learning engineers when deploying models to hardware devices?

One of the main challenges for Embedded Machine Learning Engineers is optimizing machine learning models to run efficiently on devices with limited memory, processing power, and energy capacity. Ensuring real-time performance while maintaining accuracy often requires model quantization, pruning, or using lightweight architectures. Additionally, engineers must carefully manage hardware-software integration and address issues like compatibility with various microcontrollers and ensuring secure, reliable updates for deployed models. Close collaboration with hardware engineers and software developers is essential to overcome these challenges and deliver robust embedded AI solutions.

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

AspectEmbedded Machine Learning EngineerFirmware Engineer
Required CredentialsBachelor's/Master's in Computer Science, Electrical Engineering, or related; knowledge of ML frameworksBachelor's in Electrical Engineering, Computer Engineering, or related; embedded systems experience
Work EnvironmentDevelops ML models for embedded devices, often in IoT or smart devicesDesigns and implements low-level firmware for hardware devices
Industry UsageTech companies, IoT, consumer electronics, automotiveConsumer electronics, automotive, industrial equipment

The Embedded Machine Learning Engineer focuses on integrating machine learning models into embedded systems, while the Firmware Engineer specializes in developing low-level software for hardware devices. Both roles require embedded systems knowledge but differ in their core focus and skill sets.

What are popular job titles related to Embedded Machine Learning Engineer jobs in Winnipeg, MB?

For Embedded Machine Learning Engineer jobs in Winnipeg, MB, the most frequently searched job titles are:

Senior Data Engineer

iQmetrix

Winnipeg, MB โ€ข On-site

Full-time

Retirement, PTO

Re-posted 28 days ago


Job description

What We do:
iQmetrix is a global provider of Interconnected Commerce software solutions for telecom retail. Interconnected Commerce is an AI-native telecom commerce platform that acts as a system of intelligence. It replaces fragmented legacy stacks with a modern, modular operating layer, connecting telcos, retailers, and OEMs into one flow across channels and markets. The result is less complexity, lower cost, and the speed to move ahead.
For 26 years, we’ve been passionate about helping the leading brands in telecom to grow by providing best-in-class software, services, and expertise that enables them to adapt and thrive. Our solutions power $17BN in sales annually, handling nearly 53 million invoices and more than 28 million activations, and are used by more than 370,000 telecom retail professionals across almost 1,000 clients. iQmetrix is a privately held software-as-a-service (SaaS) company with employees in Canada, the U.S., India, and Europe. For more information, please visit www.iqmetrix.com.
How We Do it: 
We are on a self-management journey. As we work to move away from the restrictions of hierarchy, teams are building collaborative peer-based networks where there are no bosses. Decisions are meant to be distributed to the people who are best able to make the decisions which means more freedom for individuals to contribute at their highest levels. We are purpose-driven, helping individuals connect to the meaning in their day-to-day work. Additionally, we are currently on the road to building a diverse and inclusive environment. Working at iQmetrix means always looking at ways to be better.
Reports To: Technical Lead
Salary: Starting at $110,000 CAD, commensurate with experience.
About the Team:
The Data & Analytics team is moving from a legacy reporting model to a modern data platform organization, one that powers embedded analytics, operational data products, and AI/ML capabilities across our SaaS point-of-sale (POS) and retail management system (RMS) ecosystem.
The team builds on cloud-native lakehouse infrastructure to create trusted, reusable, and scalable data foundations that support internal decision-making, customer-facing product experiences, and emerging AI use cases. Pipelines, data products, and platform patterns are all in scope.
 
A core part of the mission is reducing friction across the data lifecycle: onboarding, modeling, governance, exposure, and application. That means building high-quality lakehouse pipelines, enforcing rigorous data quality standards, and creating engineering patterns that let analytics, product, engineering, and AI initiatives move faster with more confidence.
About the Role:
The Senior Data Engineer will design, build, and improve the data platform capabilities that power analytics, embedded reporting, operational data products, and AI-ready datasets.
 
This role goes beyond pipeline implementation. It includes data modeling, platform design, performance tuning, governance, observability, and the creation of reusable engineering patterns that support scalable and trustworthy data products.
 
The ideal candidate is a hands-on engineer with strong production experience in Python, SQL, and distributed compute environments. They should have deep familiarity with modern lakehouse patterns and layered data product design, and should be comfortable providing technical leadership through mentoring, design reviews, code reviews, and platform stewardship.
What You'll Be Doing:
 
  • Design, build, and optimize scalable data pipelines and curated data products using Python, SQL, and distributed compute - with a strong understanding of execution models, partitioning, and performance tuning.
  • Develop and maintain data models across raw, refined, and curated layers to support reporting, embedded analytics, operational workflows, machine learning, and emerging AI use cases.
  • Build reliable, reusable, and well-documented data assets consumed by analytics, product, engineering, and downstream platform teams.
  • Design data structures that support multi-tenant SaaS reporting, dimensional modeling, semantic analytics, and governed access patterns across multiple products and customer boundaries.
  • Own orchestration using asset-based or software-defined orchestration patterns - where pipelines are modeled as versioned, observable data assets with clear ownership and dependency contracts, not just task graphs.
  • Improve the performance, reliability, observability, and cost efficiency of data processing workflows across the platform.
  • Implement and advance data quality, lineage, governance, and secure access control practices using modern lakehouse tooling and platform standards.
  • Partner with product, software engineering, analytics, and AI stakeholders to translate business workflows into reliable data products and platform capabilities.
  • Contribute to platform architecture decisions, reusable engineering patterns, data onboarding standards, and the ongoing evolution of the organization's data platform strategy.
  • Support event-oriented and near-real-time data patterns where needed to enable downstream operational and product use cases.
  • Troubleshoot complex data issues, lead root-cause analysis, and improve the resilience of pipelines, jobs, and platform services.
  • Operate comfortably within containerized or cloud-native platform infrastructure, including understanding how data services interact with surrounding platform components.
  • Mentor junior and intermediate engineers, review code and designs, and help establish best practices for data engineering, analytics enablement, and AI/ML-supporting data workflows.

What We're Looking For:
 
  • 5+ years of experience in data engineering, software engineering, analytics engineering, or a closely related field.
  • Strong proficiency in SQL and Python, with production experience in distributed compute environments and a solid understanding of execution models, partitioning, and optimization.
  • Hands-on experience with cloud-native lakehouse platforms and modern data lake storage patterns, including Delta Lake or equivalent.
  • Strong opinions about layered data product design - specifically separation of concerns between raw, refined, and curated data - and experience enforcing those boundaries at scale in a governed environment.
  • Experience designing, building, and maintaining production ETL/ELT pipelines for analytical or operational workloads.
  • Strong understanding of data modeling concepts, including dimensional modeling, curated data products, and semantic-ready data structures.
  • Familiarity with asset-based or software-defined orchestration approaches, version control, CI/CD practices, and production support for data systems.
  • Strong understanding of data quality, observability, governance, lineage, and secure data access patterns.
  • Ability to communicate technical trade-offs clearly and partner effectively across engineering, product, analytics, and business teams.
  • Experience mentoring other engineers through code reviews, design reviews, troubleshooting, and shared engineering standards.

Nice To Have:
 
  • Experience with Unity Catalog or equivalent metadata and governance layers in a cloud data platform.
  • Experience with event-driven, streaming, or near-real-time data patterns in cloud or lakehouse ecosystems.
  • Experience building data products that directly support predictive model development - including feature preparation, label definition, and pipelines that feed model training and evaluation workflows.
  • Experience supporting generative AI or agent workflows through structured and unstructured data preparation, retrieval patterns, or evaluation datasets.
  • Experience working in a SaaS product organization with multiple products, domains, tenants, or customer-specific data boundaries.
  • Familiarity with cost optimization practices for cloud data platforms.

What We Offer:

  • Begin your journey with a competitive starting salary! 
  • Enjoy peace of mind with a comprehensive benefits package for you and your entire family. 
  • Embrace work-life harmony with a flexible hybrid working environment, generous vacation and trusted sick leave program. 
  • Invest in your future with our RRSP/401K/PF and Share Ownership plans. What's even better? We offer a match program!
  • We care about your family, offering maternity, adoption, and paternity leave salary top ups as well as ten “New Baby Days” for all parents welcoming a new child into their life.  
  • Enjoy a “Cultural Day” off annually to celebrate a day of religious or cultural significance. 
  • Give back with up to 6 days of paid time off annually for volunteering or personal learning. 
  • We believe in the value of taking time to refresh, re-energize, and reflect on your career journey. Employees are granted a seven-week sabbatical after every seven years of employment! 

What is an iQer?

An iQer is a term, used daily across all iQmetrix locations, is someone who works for iQmetrix. Sounds simple, but there’s more to being an iQer than meets the eye!

If you’re an iQer, you approach problems with humility and an open mind. You’re a go-getter who doesn’t wait around to be told what do to. Whether it’s on your own or with a team, you aren’t afraid to try new things, fail, succeed, and improve along the way. Your team, the company, and the well-being of others come before your personal agenda—you’re an ally to your colleagues and the community.

The world changes fast and, as an iQer, you’re ready to adapt. You recognize diversity in the world, listen to others, and consider all perspectives.

Want to Join the Team? 

If you’re interested in a career with iQmetrix, please submit your resume and cover letter. We are an equal opportunity employer. We do not discriminate based on race, faith, colour, cultural background, gender, sexual orientation, age, marital status, or disability status. We thank all applicants for their interest, however, only those selected for an interview will be contacted. 

We are a hybrid work environment, remote and in-office for all employees in an office city.

You can view our job applicant privacy policy here.

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