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Remote Embedded Jobs in Edmonton, AB (NOW HIRING)

Remote Embedded information

See Edmonton, AB salary details

$31.5K

$124.1K

$174.5K

How much do remote embedded jobs pay per year?

As of Sep 1, 2026, the average yearly pay for remote embedded in Edmonton, AB is $124,051.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,500.00 and $145,500.00 per year, depending on experience, location, and employer.

What are remote embedded jobs?

Remote embedded jobs involve designing, developing, and maintaining embedded systems software or firmware, while working from a location outside of a traditional office—often from home. These roles typically require expertise in programming languages such as C or C++ and familiarity with hardware interfaces, microcontrollers, and real-time operating systems. Remote embedded engineers collaborate with teams using online tools and may work on products ranging from consumer electronics to automotive or industrial devices. The remote aspect allows for flexible work arrangements and access to a broader range of job opportunities across the globe.

What are remote embedded jobs?

Remote embedded jobs include positions within the software and development industry that focus on engineering, developing, and maintaining software for embedded systems and networks. Common titles include “remote embedded software engineer” and “remote embedded developer.” Embedded software has a specific task related to the operations of a hardware system. As an embedded software engineer who works from home, your duties include coding software to perform a particular function, such as the control of a piece of machinery or the collection of data from a system. As a remote embedded software developer, you perform a similar job and sometimes help clients customize embedded software. You may also work as a remote quality assurance engineer where your responsibilities involve testing existing software.

What are the key skills and qualifications needed to thrive as a remote embedded engineer, and why are they important?

To thrive as a Remote Embedded Engineer, you need a solid background in embedded systems design, programming in C/C++, and a relevant degree in electrical engineering, computer engineering, or a related field. Familiarity with hardware debugging tools, version control systems like Git, and real-time operating systems (RTOS) is typically required. Strong problem-solving abilities, effective communication skills, and the ability to work independently are essential soft skills for remote collaboration. These skills and qualities are crucial for developing reliable embedded solutions and ensuring seamless teamwork across distributed environments.

How does a remote embedded engineer typically collaborate with cross-functional teams while working offsite?

Remote Embedded Engineers often work closely with hardware, software, and quality assurance teams, even when not physically present. Collaboration is facilitated through regular video meetings, shared documentation, and version control systems like Git. Effective communication is crucial, as tasks such as debugging hardware remotely or reviewing code require clear coordination. Many teams use project management tools to track progress and ensure alignment, allowing remote engineers to contribute seamlessly to product development and problem-solving.

What is the difference between Remote Embedded vs Remote Firmware Developer?

AspectRemote EmbeddedRemote Firmware Developer
Required CredentialsBachelor's in Electrical Engineering, Computer Science, or related field; experience with embedded systemsSimilar credentials, often with additional certifications in firmware development or microcontroller programming
Work EnvironmentDesigning and testing embedded systems, often involving hardware integrationDeveloping low-level firmware for microcontrollers or hardware devices
Industry UsageElectronics, automotive, IoT, consumer devicesConsumer electronics, industrial equipment, IoT devices
Search & Comparison IntentLooking for roles involving embedded system design and softwareFocusing on firmware coding and microcontroller programming

Remote Embedded roles typically involve designing and testing embedded systems that integrate hardware and software, while Remote Firmware Developers focus specifically on writing low-level firmware for microcontrollers. Both roles require similar credentials and are used across industries like electronics and IoT, but their core responsibilities differ in hardware interaction versus firmware coding.

Is remote embedded systems still a good career?

Remote embedded systems engineering remains a viable career due to ongoing demand for expertise in hardware-software integration, IoT development, and real-time systems. Skills in C/C++, debugging tools, and familiarity with hardware platforms are valuable, and remote work options are increasingly available in this field.

What are popular job titles related to Remote Embedded jobs in Edmonton, AB?

For Remote Embedded jobs in Edmonton, AB, the most frequently searched job titles are:

What job categories do people searching Remote Embedded jobs in Edmonton, AB look for?

The top searched job categories for Remote Embedded jobs in Edmonton, AB are:

What cities near Edmonton, AB are hiring for Remote Embedded jobs?

Cities near Edmonton, AB with the most Remote Embedded job openings:

Infographic showing various Remote Embedded job openings in Edmonton, AB as of August 2026, with employment types broken down into 1% Internship, 88% Full Time, 9% Part Time, and 2% Contract. Highlights an 83% Physical, 5% Hybrid, and 12% Remote job distribution, with an average salary of $124,051 per year, or $59.6 per hour.

Software Engineer - AI/ML & LLM - Remote

YO AI Labs

Edmonton, AB • Remote

$80 - $120/hr

Full-time

Posted 6 days ago


Job description

Senior Software Engineer

Job Type: Contractor (~15 hours/week)
Location: Remote

Job Summary

We are seeking experienced Senior Software Engineers to support an AI training project by creating reinforcement learning environments that evaluate AI models on complex software engineering tasks using Model Context Protocol (MCP) tools.

You will design reproducible environments, deterministic verification, and reference solutions for tasks such as bug fixing, feature implementation, codebase refactoring, and performance optimization. No prior AI experience is required.

Key Responsibilities
  • Create reinforcement learning environments for software engineering tasks.
  • Design tasks involving bug fixing, feature development, refactoring, and performance optimization.
  • Build deterministic verification systems and golden reference solutions.
  • Evaluate AI agents' ability to reason through complex codebases and use MCP tools effectively.
  • Develop realistic, reproducible software engineering scenarios.
  • Ensure tasks accurately measure coding ability, problem-solving, and tool usage.
  • Document solutions and provide clear technical feedback.
Required Skills
  • Strong proficiency in Python 3, Java, Rust, C++, or TypeScript.
  • Strong understanding of algorithms and data structures.
  • Experience with bug fixing and debugging complex software issues.
  • Proven experience in feature implementation and codebase refactoring.
  • Strong knowledge of performance optimization and tuning.
  • Excellent written and verbal communication.
  • Strong attention to detail.
Preferred Qualifications
  • Experience working with large-scale or distributed codebases.
  • Familiarity with AI/ML systems is a plus but not required.
  • Experience with rigorous code reviews and software engineering best practices.
  • Experience working effectively in remote or cross-functional teams.
Hiring Process
  1. Submit an application and screening questions.
  2. Complete an AI interview (~30 minutes).
  3. Complete a technical assessment, if required.
  4. Hiring Manager review.
Compensation

Compensation is output-based, with payment provided per task that meets project specifications. Minimum weekly submission requirements may apply.

Availability

Selected experts should be prepared to begin their first tasks within 24–48 hours of completing onboarding.