1

Environmental Modeling Jobs in Alberta (NOW HIRING)

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 ...

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 ...

... environments. Operating across workplace, healthcare, education, and public sector markets, DIRTT ... Create 3D models, CAD drawings, prototypes, and manufacturing information, maintaining a high level ...

Showing results 41-60

Environmental Modeling information

See Alberta salary details

$20.5K

$84.2K

$180K

How much do environmental modeling jobs pay per year?

As of Sep 9, 2026, the average yearly pay for environmental modeling in Alberta is $84,220.00, according to ZipRecruiter salary data. Most workers in this role earn between $48,500.00 and $107,000.00 per year, depending on experience, location, and employer.

What is an environmental modeling job?

An Environmental Modeling job involves using computer models and simulations to study environmental systems and predict changes due to natural or human influences. Professionals in this field analyze data related to climate change, pollution, water resources, and ecosystems to support decision-making in policy, conservation, and resource management. They often work with geographic information systems (GIS), statistical analysis tools, and programming languages to develop accurate models. Environmental modelers collaborate with scientists, engineers, and policymakers to address environmental challenges and create sustainable solutions.

What are the key skills and qualifications needed to thrive in environmental modeling?

To thrive in Environmental Modeling, you need a solid background in environmental science, mathematics, and computer programming, often supported by a relevant degree such as environmental engineering or earth sciences. Familiarity with modeling software like MATLAB, ArcGIS, or Python, as well as certifications in GIS or environmental data analysis, is highly valued. Strong analytical thinking, attention to detail, and effective communication skills enable you to interpret complex data and collaborate with multidisciplinary teams. These competencies are essential for producing reliable models that inform environmental policy, planning, and sustainability efforts.

What are some common challenges faced in environmental modeling roles?

Professionals in Environmental Modeling often deal with challenges such as managing incomplete or inconsistent environmental data, staying updated with rapidly evolving modeling technologies, and interpreting complex results for non-technical stakeholders. You may also encounter tight deadlines when responding to environmental incidents or regulatory changes. Overcoming these challenges involves continuous learning, creative problem-solving, and clear communication with scientists, engineers, and policymakers. These aspects can make the role demanding but also provide opportunities for professional growth and meaningful impact.

What job categories do people searching Environmental Modeling jobs in Alberta look for?

The top searched job categories for Environmental Modeling jobs in Alberta are:

Infographic showing various Environmental Modeling job openings in Alberta as of August 2026, with employment types broken down into 1% As Needed, 81% Full Time, 15% Part Time, 2% Contract, and 1% Nights. Highlights an 93% Physical, 3% Hybrid, and 4% Remote job distribution, with an average salary of $84,220 per year, or $40.5 per hour.

RL Environment Engineer - Remote

Calgary, AB โ€ข Remote

$80 - $120/hr

Full-time

Posted 12 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.