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Remote Complete Call Solutions Jobs in Toronto, ON

You will design reproducible environments, deterministic verification, and reference solutions for ... Complete an AI interview (~30 minutes). * Complete a technical assessment, if required. * Hiring ...

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... solutions for some of the world's most recognized brands. Our agents play a key role in ensuring ... · Call center or high-volume service experience preferred · Hospitality, travel, or loyalty ...

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Call center environments * Education * Sales and account support * Client-facing positions The ... solutions. Remote representatives communicate directly with clients while receiving training ...

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Remote Complete Call Solutions information

What is the difference between Remote Complete Call Solutions vs Customer Service Representative?

AspectRemote Complete Call SolutionsCustomer Service Representative
CredentialsHigh school diploma or equivalent; training in call handling and softwareHigh school diploma or equivalent; training in customer service skills
Work EnvironmentRemote, home-based call center or office settingRemote or on-site customer support centers
Industry UsageUsed across various industries for comprehensive call managementPrimarily in retail, telecom, and service sectors
Job FocusHandling multiple call types, including sales, support, and inquiriesResponding to customer inquiries, resolving issues

Remote Complete Call Solutions involves managing a wide range of call types with specialized training, often in a remote setting. Customer Service Representatives focus on assisting customers with specific issues, typically within a particular industry. Both roles require strong communication skills but differ in scope and training emphasis.

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What cities near Toronto, ON are hiring for Remote Complete Call Solutions jobs?

Cities near Toronto, ON with the most Remote Complete Call Solutions job openings:

Full Stack Software Engineer - Remote

YO AI Labs

Toronto, ON • Remote

$80 - $120/hr

Full-time

Posted 7 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.