AI Engineer

RemoteJobsOne; Toronto; Remote; CAD 117,000 - 234,000; Part time

Job summary

RemoteJobsOne is seeking an AI Engineer for a fully remote contractor role based in Canada. You will help train next-generation AI systems and design reinforcement learning environments using MCP tools, focusing on code quality, performance, and scalable solutions.

Responsibilities include implementing features, debugging complex software, and collaborating with cross-functional teams in a distributed setup. Flexible schedule and part-time commitment of about 15 hours per week are offered.

Qualifications

• Proficiency in multiple programming languages listed above.
• Strong knowledge of algorithms and data structures.
• Experience debugging complex software issues.
• Ability to work in a distributed remote team.
• Excellent written and verbal communication.

Responsibilities

• Design Reinforcement Learning Environments to test an AI model's ability to solve complex software engineering problems.
• Fix bugs, implement features, refactor code, and optimize performance while ensuring reproducible environments.
• Collaborate with cross-functional teams in a distributed, remote setting.

Skills

C++

Python

Java

Go

TypeScript

Rust

Algorithms

Data structures

Performance tuning

Debugging

Code refactoring

Remote collaboration

Job description

IMPORTANT: after you apply, please check your email. We send you a link to complete your application — it is not considered until that last step is done. If you do not see it, check your spam folder.

This is a fully remote position, open to candidates based in Canada.

Pay: $60–$120/hr

Job Title: AI Engineer

Job Type: Contractor (~15 hrs a week)

Location: Remote

Schedule: Flexible, you pick the hours and days (including weekends if desired)

Job Summary: In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.

As an expert you will be creating Reinforcement Learning Environments which test an AI model’s ability to solve complex software engineering problems using Model Context Protocol (MCP) tools. Tasks may involve fixing bugs, implementing features, refactoring code, or optimizing performance while requiring agents to discover and reason over information from real MCP servers. You will design reproducible environments, deterministic verification, and golden reference solutions that accurately measure both MCP tool use and software engineering ability.

Required Skills and Qualifications:

1. Proficiency in C++, Python, JAVA, GoLang, Typescript, or Rust.
2. Deep understanding of algorithms, data structures, and performance tuning.
3. Demonstrated experience in debugging complex software issues and delivering maintainable solutions.
4. Strong background in feature development and codebase refactoring.
5. Proven ability to optimize software for performance and scalability.
6. Exceptional written and verbal communication skills, with a keen attention to detail.
7. Track record of success in collaborative, cross-functional teams, ideally in remote settings.

Preferred Qualifications:

1. Previous experience working on large-scale, distributed codebases.
2. Familiarity with modern AI or machine learning systems is a plus, though not required.
3. Background in participating in rigorous code reviews and contributing to the development of software best practices.

Process:

1. Apply to the role, filling out the screening questions
2. Complete AI Interview (approx. 30 minutes)
3. Technical Assessment (Tentative)
4. Hiring Manager review

Compensation Structure

Compensation is output-based; experts are paid per task that meets the project specifications. The time required to complete work may vary depending on the expert’s experience and workflow. Minimum submission requirements apply. Experts must submit a minimum of tasks per week.

Start Timeline & Availability

We typically fill roles within 48 hours and are looking for experts ready to jump in right away. If selected, we expect you to start your first tasks within 24–48 hours of completing onboarding.