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Machine Learning Teaching Assistant Jobs in Calgary, AB

Clio

Manager, Machine Learning Engineering

Calgary, AB · Remote

CA$181K - CA$272K/yr

We are currently seeking a Manager, Machine Learning Engineering to join our rapidly growing ... Teach and learn from those around you, providing constructive feedback and taking on feedback to ...

NRG Energy

Data Scientist

Calgary, AB · On-site

... and AI assistants. * Experience with Azure OpenAI, Databricks, MLflow, Azure AI, or similar cloud-based AI platforms. * Strong understanding of statistics, machine learning, forecasting, and ...

NRG

Data Scientist

Calgary, AB · On-site

... and AI assistants. * Experience with Azure OpenAI, Databricks, MLflow, Azure AI, or similar cloud-based AI platforms. * Strong understanding of statistics, machine learning, forecasting, and ...

Elkay Manufacturing

Machine Operator II

Calgary, AB · On-site

Focuses on learning additional tasks and ensuring quality at all times. * Perform repetitive tasks ... Demonstrates some leadership skills through informal coaching and teaching others * Ability ...

Gaf

Learning and Development Instructor

Calgary, AB · On-site

This team consists of instructors who teach to every level of the industry from single-roofer start ... Job Summary An External Learning & Development Instructor is responsible for running training ...

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All JobsMachine Learning Teaching JobsMachine Learning Teaching Assistant JobsMachine Learning Teaching Assistant Jobs in Calgary, AB

Machine Learning Teaching Assistant information

What is a machine learning teaching assistant?

Machine Learning Teaching Assistants are individuals, often graduate students or knowledgeable undergraduates, who assist professors or instructors in teaching machine learning courses. Their responsibilities typically include helping students understand course material, grading assignments, holding office hours, and sometimes leading discussion or lab sessions. They act as a bridge between students and instructors, offering support for both theoretical concepts and practical implementation. By providing guidance and feedback, they help ensure students gain a solid understanding of machine learning principles and applications.

How does a machine learning teaching assistant typically collaborate with professors and students during a course?

As a Machine Learning Teaching Assistant, you will work closely with professors to develop and grade assignments, clarify course concepts, and facilitate discussions in lectures or lab sessions. You often serve as a bridge between students and faculty, providing guidance on programming tasks, troubleshooting code, and offering feedback on projects. Regular office hours and online forums are common venues for this support, making strong communication skills and a solid grasp of machine learning fundamentals essential. This collaborative environment helps you deepen your expertise while supporting student learning.

What are the key skills and qualifications needed to thrive as a machine learning teaching assistant, and why are they important?

To thrive as a Machine Learning Teaching Assistant, you need a solid foundation in machine learning concepts, programming (often Python), and relevant coursework or a degree in computer science or a related field. Familiarity with tools like Jupyter Notebooks, TensorFlow, PyTorch, and version control systems is commonly expected. Strong communication, patience, and organizational skills help you effectively support students and collaborate with instructors. These abilities ensure you can explain complex topics clearly, assist students efficiently, and contribute to a positive learning environment.
Machine Learning Teaching Assistant jobs near you
Infographic showing various Machine Learning Teaching Assistant job openings in Calgary, AB as of August 2026, with employment types broken down into 1% As Needed, 64% Full Time, 32% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Senior Machine Learning Engineer

Calgary, AB • On-site

Fullscript
See more jobs at Fullscriptexternal

Full-time

Retirement, PTO

Posted yesterday

New

Job description

About Fullscript
 
We're an industry-leading health technology company on a mission to help people get better. We started in 2011 with one simple idea. Make it easier for practitioners to access the products they trust so they can deliver better care.
 
That simple idea grew into a platform that powers every part of care. Today, more than 125,000 practitioners use Fullscript for clinical insights, lab interpretations, patient analytics, education, and access to high-quality supplements. Over 10 million patients rely on Fullscript to stay connected to their care plans and follow through on treatment.
 
We build tools that make care smarter and more human. Tools that save time, simplify decisions, and help practitioners stay closely connected to the people they care for. When everything they need is in one place, they can focus on what matters most: helping people get better.
 
This is your invitation.
 
Bring your ideas, your grit, and your care for people.
Join us and shape the future of care.

The Opportunity

We're hiring a Senior Machine Learning Engineer to join our AI & Analytics Engineering team. This team builds AI-powered lab interpretation, clinician decision support, and conversational experiences directly into the Fullscript product.

You'll help build the systems behind some of Fullscript's most important AI experiences: AI-generated lab summaries, practitioner-facing conversational agents, and tools that help clinicians move from data to insight more quickly. The work is technical, product-minded, and deeply tied to real practitioner workflows.

This is a senior individual contributor role for someone who has shipped production AI systems, understands how to turn ambiguous clinical and product problems into working software, and can own work from early experimentation through deployment, evaluation, and iteration.

You'll work closely with engineering, product, analytics, and medical stakeholders to build AI features that are reliable, useful, and grounded in the way practitioners actually deliver care.

What you'll do
  • Design, build, and deploy LLM-powered product features, including lab result summaries, clinical workflow tools, and practitioner-facing conversational agents.
  • Build backend services that integrate LLMs and ML models into Fullscript's platform, primarily using Python, with increasing exposure to Elixir as the platform evolves.
  • Develop AI systems that can support open-ended clinical questions, follow-up interactions, and reasoning over structured and unstructured healthcare context.
  • Implement prompting, grounding, retrieval, and safety strategies that improve output quality, consistency, and clinical relevance.
  • Build evaluation, testing, monitoring, and CI/CD workflows for AI features, including approaches for accuracy, hallucination detection, edge cases, and reliability.
  • Partner with medical, product, analytics, and engineering teams to translate clinical needs into practical AI capabilities that can scale.
  • Own AI systems end to end, from experimentation and prototyping through production deployment, iteration, and ongoing improvement.
  • Contribute to architecture and implementation decisions for AI-powered analytics, lab interpretation, and clinical decision-support workflows.
  • Stay current with fast-moving LLM, agentic AI, and applied ML ecosystems, while staying pragmatic about what is ready for production use.
What you bring to the table
  • 7+ years of experience in machine learning engineering, applied AI engineering, backend engineering, or a similar role, with a track record of shipping production systems.
  • 2+ years of recent hands-on experience building LLM-powered applications, including conversational agents, RAG workflows, tool use, or agentic systems.
  • Strong backend development experience in Python, with solid SQL fundamentals and comfort working across data-heavy product environments.
  • Familiarity with MCP, Langfuse, agent orchestration patterns, tool-calling systems, or multi-step AI workflows.
  • Experience integrating LLMs such as OpenAI, Gemini, Anthropic, or similar models into user-facing products.
  • Experience with LLM application frameworks or orchestration tools such as LangChain, LangGraph, Hugging Face tools, or similar frameworks.
  • Strong engineering practices, including Git, testing, CI/CD, observability, evaluation, and production monitoring.
  • Experience evaluating and validating LLM-based applications for quality, hallucinations, correctness, edge cases, and reliability over time.
  • Ability to work independently in ambiguous problem spaces, ask strong questions, make sound tradeoffs, and partner effectively with technical, product, medical, and non-technical stakeholders.
Bonus if you have
  • Experience building AI assistants, conversational agents, or decision-support tools in healthcare, clinical workflows, regulated products, or other high-trust environments.
What we can offer you
  • Flexible PTO and competitive pay, because work-life balance matters
  • RRSP/401k match and stock options to invest in your future
  • Premium benefits package with customizable coverage, paramedical services, and an HSA.
  • Fullscript discounts to save on high-quality wellness products
  • Continuous learning opportunities to grow your skills and career
  • Remote-first flexibility to work where you work best, with Ottawa, Toronto, or Calgary preferred for this role.
Compensation Range
The salary range for this role is between $140,000 to $160,000 CAD. Fullscript shares salary ranges to support transparency and help candidates make informed decisions. The range shown reflects base salary only. The range shown reflects base salary only. Additional incentives, perks, and benefits may be available as part of Fullscript's total rewards package.

Final base salary depends on experience, skills, and location. We review pay regularly to stay aligned with market data and internal equity. Benefits and total rewards may vary by region.
Why Fullscript
 
Great work happens when people feel supported, trusted, and inspired. At Fullscript, we stay curious and keep finding smarter ways to make care better. We grow together, take on new challenges, and focus on impact. We put people first, work as a team, and leave egos at the door.
 
What to Know Before You Apply
 
We're grateful for the interest in joining Fullscript. To make sure your application reaches our hiring team, please apply directly through our careers page.
A quick note: Due to the high volume of applications, we're not able to respond to phone or email inquiries about application status. If there's a match, our team will reach out directly.
 
Fullscript is an equal opportunity employer committed to creating an inclusive workplace. Accommodations are available upon request at [email protected].
 
All offers are contingent on successful background checks conducted in compliance with federal, state, and provincial laws.
 
We use AI tools to support parts of the hiring process, including screening and reviewing responses. Final hiring decisions are always made by people and follow all applicable privacy and employment laws in Canada and the U.S.
 
Learn More
 
www.fullscript.com
@fullscriptHQ on instagram
Let's make healthcare whole 
 
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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