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Added 12 mins ago
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Amii (Alberta Machine Intelligence Institute)

Applied Research Scientist

AB, Canada
Edmonton, AB, Canada

Full-time

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Job details

Job type: Full-time
Apply by: Nov 27, 2026
Posting language: English
Posted: Oct 28, 2026

Original job description

“This role offers a unique opportunity to contribute to cutting-edge AI research in Trust and Safety, with a particular focus on understanding and evaluating the risks of autonomous AI systems. You’ll collaborate with researchers and practitioners to advance the science of AI safety and translate research into practical tools and approaches that support safer AI development and adoption. There is so much meaningful work ahead, and we’re eager to build it together.”

Alyssa Lefaivre Škopac | Director, AI Trust and Safety

About Amii

One of Canada’s three main institutes for artificial intelligence (AI) and machine learning, our world-renowned researchers drive fundamental and applied research at the University of Alberta (and other academic institutions), training some of the world’s top scientific talent. Amii is a core partner in the Canadian AI Safety Institute (CAISI). Our cross-functional teams work collaboratively with Alberta-based businesses and organizations to build AI capacity and translate scientific advancement into industry adoption and economic impact.

About The Role

The Applied Research Scientist will advance the understanding and safety of increasingly autonomous AI systems through research on agentic AI. The role will investigate key safety challenges, develop rigorous evaluation methods, and explore approaches to improving system reliability, robustness, and oversight.

Reporting to the Director of AI Trust and Safety, the Applied Research Scientist will lead research to understand, evaluate, and mitigate risks associated with agentic AI systems.

As AI systems evolve from responding to individual prompts to independently planning, making decisions, using tools, and executing complex tasks, new safety challenges are emerging. This role will advance scientific understanding of these challenges and develop practical approaches to addressing them.

Research will build on Amii’s strengths, address critical gaps in the AI safety landscape, and be informed by national and international research priorities. Outputs will include academic papers, whitepapers, conference presentations, open-source tools, and evaluation methodologies.

The position focuses on achieving excellence in three main accountabilities:

Trust & Safety AI Research Projects
Strategy & Applied Expertise
Project Execution

Potential Research Focus Areas May Include

Agentic AI safety evaluations: Developing rigorous methodologies, benchmarks, and testing environments to assess the capabilities, risks, robustness, and reliability of increasingly autonomous AI systems, including their behaviour across complex tasks and environments.
Goal misgeneralization and unintended behaviours: Investigating how agentic systems interpret and pursue objectives, including failures where behaviours diverge from intended goals, instructions, or constraints.
Oversight, monitoring, and control: Exploring approaches to evaluating and improving human oversight, monitoring, intervention, and control of autonomous AI systems.
Emerging agentic safety risks: Investigating novel safety challenges associated with agentic AI, including failures arising from tool use, long-horizon tasks, interactions with external environments, and increasingly complex agent architectures.

These focus areas are intended to guide, rather than limit, the research agenda. We welcome candidates who bring new perspectives, methodologies, and research questions that could meaningfully advance the science of agentic AI safety.

Required Skills / ExpertiseKey Responsibilities

Develops and communicates a clear vision for how research projects contribute to the goals of the T&S program at Amii, which may include applied industry projects
Proposes, develops and executes Trust & Safety research proposals, defining objectives, scope, methodologies, evaluation approaches, and resource needs, with a particular focus on agentic AI safety.
Develops and implements research experiments, evaluation pipelines, and environments, working with engineering colleagues where appropriate
Identifies opportunities throughout the research process to translate findings into practical evaluation tools, methodologies, frameworks, and applications
Authors and publishes peer-reviewed papers, whitepapers, and other scientific outputs
Evaluates results and emerging insights to refine research plans and determine whether to continue, pivot, or discontinue projects based on research findings, new insights, technologies, or shifts in industry trends
Represents the organization at conferences, workshops, and industry events, sharing knowledge and building a reputation as a thought leader in AI T&S
Mentors junior team members, providing technical guidance and strategic advice on T&S projects
Collaborates with cross-functional teams, coordinates project timelines, and resolves challenges to ensure project success
Supports collaborations with Canadian and international research institutions to expand the scope and impact of T&S research
Leads and/or supports applications for additional funding, including grant proposals, research applications etc.
Supports with reporting requirements and generating insights on our trust and safety impact for key funding and government bodies

Qualifications:

Ph.D. in Machine Learning, Artificial Intelligence, Computer Science, or a related field
- Candidates with a Master’s degree and extensive industry experience may also be considered
2+ years of post-PhD research experience developing, training and evaluating machine learning systems in an applied or industry setting, including demonstrated research outputs (e.g. peer-reviewed publications, open-source tools, benchmarks etc.)
Demonstrated research experience or substantial technical exposure in AI safety, including familiarity with emerging safety risks, evaluation methodologies, and research priorities
Strong knowledge of modern AI and machine learning, with particular familiarity with agentic AI systems, including LLM-based agents, tool use, autonomous decision-making, or related architectures
Experience leading research projects from question to publication or deployment, including contributions to peer-reviewed ML/AI conferences, journals, or other recognized scientific outputs
Experience developing, implementing, and evaluating ML models or AI systems, particularly in industry or applied settings
Proficiency in Python and ML frameworks (e.g., PyTorch, TensorFlow, JAX), and familiarity with AI experimentation and evaluation tooling, including model APIs, open-source models, agent frameworks, experiment tracking, and computational infrastructure
Ability to clearly communicate complex technical concepts and research findings to both technical and non-technical audiences

Knowledge, Skills and Abilities:

Demonstrates presence, self-confidence, sound judgment, and superior problem-solving ability
Thrives in ambiguity, bringing intellectual curiosity and scientific rigour to emerging research areas where the questions, methods, and best practices are still taking shape.
Strong interpersonal communication skills for effective interactions with internal departments and external stakeholders
A motivated leader who demonstrates individual drive and an uncompromising desire to achieve exceptional results
Demonstrated ability to work independently, exercise sound scientific judgment, and navigate emerging research areas where methodologies are still evolving.
Promotes high-level cross-functional collaboration and establishes credibility while influencing peers to achieve common goals
Demonstrates professional maturity, resourcefulness and self-discipline in engaging in the pursuit of the organization’s goals
Active participation in the research community: publishing research, serving as research reviewers, supporting Amii students, speaking or teaching within their area of expertise

What you'll love about us

A professional yet casual work environment that encourages the growth and development of your skills
Participate in professional development activities
Gain access to the Amii community and events
A chance to learn from amazing teammates who support one another to succeed
Competitive compensation, including paid time off and flexible health benefits
A modern office located in downtown Edmonton, Alberta

How to Apply

If this sounds like the opportunity you've been waiting for, please don’t wait to apply - we’re excited to add a new member to the Amii team for this position. We are keeping the door open to new applicants until we find the right fit. When sending your application, please send your CV and cover letter indicating why you think you'd be a fit for Amii. In your cover letter, please also indicate how your research expertise supports Amii’s Trust and Safety research priorities and addresses a gap in the current research landscape.

Applicants must be legally eligible to work in Canada at the time of application.

Amii is an equal opportunity employer and values a diverse workforce. We encourage applications from all qualified individuals without regard to ethnicity, religion, gender identity, sexual orientation, age or disability. Accommodations for disability-related needs throughout the recruitment and selection process are available upon request. Any information provided by you for accommodations will be kept confidential and won’t be used in the selection process.

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More about this job

Responsibilities

Lead research to understand, evaluate, and mitigate risks in agentic AI systems, including developing experiments, evaluation methods, and practical safety tools. Publish and present research, mentor team members, collaborate with research and industry partners, and support funding applications and impact reporting.

Requirements

A PhD in machine learning, artificial intelligence, computer science, or a related field is required, though candidates with a master’s degree and extensive industry experience may also be considered; the role also asks for at least two years of post-PhD applied or industry research experience. Candidates should have AI safety and agentic AI expertise, experience leading research through publication or deployment, proficiency in Python and ML frameworks, and strong communication and collaboration skills.

Skills

Agentic AI Safety
AI Safety Research
Machine Learning
Artificial Intelligence
Research Project Leadership
Safety Evaluation Methodologies
Benchmark Development
Python
PyTorch
TensorFlow
JAX
LLM-Based Agents
Tool Use
Experimentation and Evaluation Tooling
Scientific Communication
Cross-Functional Collaboration

Benefits

Paid Time Off
Flexible Health Benefits
Professional Development
Access to Amii Community and Events

Visa sponsorship

Not detected in the job text

Hiring contact

Alyssa Lefaivre Škopac

Keywords

Trust and Safety
AI Safety
Agentic AI
Autonomous AI Systems
Machine Learning
Artificial Intelligence
Large Language Model Agents
Tool Use
Autonomous Decision-Making
Safety Evaluations
Evaluation Methodologies
Benchmarks
Testing Environments
Goal Misgeneralization
Unintended Behaviors
Oversight
Monitoring
Control
Robustness
Reliability
Python
PyTorch
TensorFlow
JAX
Open-Source Models
Agent Frameworks
Experiment Tracking
Computational Infrastructure
Research Publications
Grant Proposals

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