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Junior Machine Learning Engineer Jobs in Alberta

Fullscript

Staff, Machine Learning Engineer

Calgary, AB · On-site +1

The Opportunity We're hiring a Staff Machine Learning Engineer to join our AI team and help shape the next generation of Fullscript's AI-powered experiences. You'll work on building innovative AI ...

General Motors

Senior AI/ML Engineer

Mountain View, AB · On-site +1

CA$170K - CA$261K/yr

... machine learning priorities into concrete, actionable prototypes. * Provide technical mentorship to junior researchers and engineers, fostering a culture of excellence and collaborative innovation.

DataVisor

Senior Software Engineer - Canada

Calgary, AB · Remote

CA$120K - CA$150K/yr

Its patented unsupervised machine learning technology, advanced device intelligence, powerful ... As platform engineers, we are building a next-generation machine learning platform, which ...

BigGeo

Spatial AI Engineer

Calgary, AB · On-site

The RoleThe Spatial AI Engineer builds the systems that let AI models, applications, and ... You will design and implement machine learning systems that operate directly on spatial datasets ...

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All JobsMachine Learning Engineer JobsJunior Machine Learning Engineer JobsJunior Machine Learning Engineer Jobs in Alberta

Junior Machine Learning Engineer information

See Alberta salary details

$26K

$119.2K

$207.5K

How much do junior machine learning engineer jobs pay per year?

As of Jun 10, 2026, the average yearly pay for junior machine learning engineer in Alberta is $119,158.00, according to ZipRecruiter salary data. Most workers in this role earn between $90,500.00 and $149,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Junior Machine Learning Engineer, and why are they important?

To succeed as a Junior Machine Learning Engineer, you need a solid grasp of programming (especially Python), foundational knowledge of algorithms and statistics, and a relevant degree in computer science, mathematics, or a related field. Familiarity with machine learning frameworks such as TensorFlow or PyTorch and tools like scikit-learn, as well as experience with version control systems like Git, are typically required. Strong problem-solving abilities, attention to detail, and a willingness to learn from feedback are valuable soft skills that help you adapt and grow in the field. These skills ensure you can effectively develop, test, and improve machine learning models while collaborating with more experienced engineers and contributing to team projects.

What kinds of projects and responsibilities can a Junior Machine Learning Engineer expect in their first year on the job?

As a Junior Machine Learning Engineer, you’ll typically work on tasks such as data preprocessing, building and testing simple models, and supporting more senior engineers in deploying machine learning solutions. Your responsibilities may also include cleaning datasets, implementing basic algorithms, and running experiments to evaluate model performance. You’ll often collaborate closely with data scientists, software engineers, and product teams to understand project goals and learn best practices. The role provides excellent opportunities to develop your technical skills, gain exposure to various stages of the ML pipeline, and gradually take on more complex projects as you grow.

What is the difference between Junior Machine Learning Engineer vs Data Scientist?

AspectJunior Machine Learning EngineerData Scientist
Required CredentialsBachelor's in CS, Data Science, or related; some experience with ML frameworksBachelor's or higher in CS, Statistics, or related; often advanced certifications
Work EnvironmentDeveloping and deploying ML models, coding, testingData analysis, statistical modeling, interpreting data insights
Employer & Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, tech, consulting
Search & Comparison IntentYesYes

While both roles involve working with data and machine learning, Junior Machine Learning Engineers focus on building and deploying models, often with coding and engineering skills. Data Scientists analyze data, create statistical models, and interpret insights. The roles overlap but differ mainly in their core responsibilities and skill emphasis.

What does a Junior Machine Learning Engineer do?

A Junior Machine Learning Engineer assists in developing, testing, and deploying machine learning models under the supervision of senior engineers or data scientists. Their responsibilities often include data preprocessing, feature engineering, and implementing algorithms using frameworks like TensorFlow or PyTorch. They also help maintain data pipelines and ensure models perform efficiently in production environments. This role is typically entry-level, providing valuable hands-on experience in applying machine learning concepts to real-world problems.

What Does a Junior Machine Learning Engineer Do?

As a junior machine learning engineer, you work in AI, performing research with algorithms and data modeling techniques. Machine learning involves using large collections of data to create systems that are capable of making predictions, and in this field, your duties and responsibilities revolve around using advanced mathematics to design applications for use in everything from stock trading to sports betting. Some machine learning efforts involve images, and this branch of the field is known as computer vision, while other techniques which focus on text are called natural language processing (NLP). Given these divisions, titles in machine learning include computer vision engineer, NLP scientist, or simply research scientist.

More about Junior Machine Learning Engineer jobs
What are the most commonly searched types of Machine Learning Engineer jobs in Alberta? The most popular types of Machine Learning Engineer jobs in Alberta are:
What are popular job titles related to Junior Machine Learning Engineer jobs in Alberta? For Junior Machine Learning Engineer jobs in Alberta, the most frequently searched job titles are:
What job categories do people searching Junior Machine Learning Engineer jobs in Alberta look for? The top searched job categories for Junior Machine Learning Engineer jobs in Alberta are:
What cities in Alberta are hiring for Junior Machine Learning Engineer jobs? Cities in Alberta with the most Junior Machine Learning Engineer job openings:
Junior Machine Learning Engineer jobs near you
Infographic showing various Junior Machine Learning Engineer job openings in Alberta as of June 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $119,158 per year, or $57.3 per hour.

Senior Machine Learning Engineer

Fullscript

Calgary, AB • On-site

Full-time

Retirement, PTO

Posted 5 days ago

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
  • 5+ 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.
  • 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 with Elixir, Phoenix, functional programming, or an interest in building with Elixir as Fullscript's AI platform evolves.
  • Experience building AI assistants, conversational agents, or decision-support tools in healthcare, clinical workflows, regulated products, or other high-trust environments.
  • Familiarity with MCP, Langfuse, agent orchestration patterns, tool-calling systems, or multi-step AI workflows.
What we can offer you
  • Salary range: $130,00 to $150,000 CAD
  • 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.
Fullscript shares salary ranges to support transparency and help candidates make informed decisions. The range shown reflects the approved range for this role and does not include stock options, wellness stipends, or other benefits that may be part of Fullscript's total rewards package.
 
Final compensation 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. 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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