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Deep Learning Engineer Jobs in Alberta (NOW HIRING)

Partner closely with engineering, security, and compliance functions * Present findings clearly to ... learning * Experience red teaming LLM or AI systems * Deep familiarity with AI deployment ...

... deep foundations, retaining structures and earth structures. * Conducting and reviewing slope ... Learning and development opportunities for ongoing professional growth. * Mentorship with world ...

The ideal candidate brings a deep technical mastery of SQL, DevOps, Git, Spark, Python, dataflows ... learning. Direct experience in data warehousing, ETL/ELT processes, database design with strong ...

Deep experience in data engineering, data platform, or distributed systems roles * Proven track ... that supports learning through iteration. * Applicants must currently reside within commuting ...

Senior Systems Engineer, Production

Calgary, AB · Remote

CA$176K - CA$202K/yr

... learning. * Partner with Security, MLOps, and Product Engineering teams to deliver scalable, resilient, and compliant systems. What you may have: * Deep experience designing, deploying, and operating ...

Staff Data Engineer

Calgary, AB · Remote

CA$180/hr

Deep experience in data engineering, data platform, or distributed systems roles * Proven track ... that supports learning through iteration. * Applicants must currently reside within commuting ...

Senior Data Engineer

Calgary, AB · Remote

CA$11K - CA$140K/yr

Deep SQL skills and Python experience applied to data extraction, transformation, and validation ... Continuous learning opportunities to grow your skills and career * Remote-first flexibility to work ...

The ideal candidate has a deep understanding of data analysis, Cloud engineering, machine learning, NLP techniques, along with a proven track record of delivering impactful insights and solutions.

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Deep Learning Engineer information

See Alberta salary details

$90.5K

$169.3K

$228K

How much do deep learning engineer jobs pay per year?

As of Jun 8, 2026, the average yearly pay for deep learning engineer in Alberta is $169,298.00, according to ZipRecruiter salary data. Most workers in this role earn between $151,500.00 and $188,000.00 per year, depending on experience, location, and employer.

What is a Deep Learning Engineer job?

A Deep Learning Engineer is a specialized software engineer who designs, develops, and optimizes deep learning models. They work with neural networks, large datasets, and frameworks like TensorFlow or PyTorch to build AI systems for tasks like image recognition, natural language processing, and autonomous systems. Their responsibilities include data preprocessing, model training, performance tuning, and deploying models into production. Strong programming skills in Python, knowledge of machine learning algorithms, and experience with GPU acceleration are essential for this role.

What are the key skills and qualifications needed to thrive in the Deep Learning Engineer position, and why are they important?

To thrive as a Deep Learning Engineer, you need a strong background in mathematics, machine learning theory, and programming (especially Python), often supported by a relevant degree in computer science, engineering, or related fields. Proficiency with frameworks such as TensorFlow, PyTorch, Keras, as well as experience with GPUs and cloud platforms, is highly valued, and certifications in AI or deep learning can further enhance your profile. Effective problem-solving, strong collaboration skills, and clear communication are important soft skills for excelling in interdisciplinary teams. These abilities ensure that you can develop robust deep learning models, adapt to evolving technologies, and contribute value in both technical and collaborative settings.

What are the typical daily tasks and responsibilities of a Deep Learning Engineer?

Deep Learning Engineers typically spend their days designing, developing, and optimizing neural network models for tasks like image recognition, natural language processing, or recommendation systems. They preprocess and analyze large datasets, experiment with model architectures, and tune hyperparameters to achieve the best performance. Collaboration is often required with data scientists, product managers, and software engineers to integrate models into real-world applications and scale solutions for production. Additionally, many deep learning engineers review current research, stay updated on advancements in AI, and continuously improve their skills. This role offers a dynamic work environment where learning and innovation are highly encouraged.

What are popular job titles related to Deep Learning Engineer jobs in Alberta? For Deep Learning Engineer jobs in Alberta, the most frequently searched job titles are:
What job categories do people searching Deep Learning Engineer jobs in Alberta look for? The top searched job categories for Deep Learning Engineer jobs in Alberta are:
Infographic showing various Deep Learning Engineer job openings in Alberta as of May 2026, with employment types broken down into 11% Internship, 68% Full Time, and 21% Contract. Highlights an 95% In-person, and 5% Hybrid job distribution, with an average salary of $169,298 per year, or $81.4 per hour.

Machine Learning Resident - Client: Zamplo (8 month term)

Alberta Machine Intelligence Institute

Edmonton, AB

Full-time

Posted 5 days ago


Job description

"Join us for a unique ML Resident role focusing on improving patient outcomes by predicting risk of an adverse event using ML/DL. You'll work in a fast-paced and dynamic team of machine learning scientists, healthcare providers, and domain experts ." - Soumik Farhan, Machine Learning ScientistAbout AmiiOne 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. 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 RoleThis is a paid residency that will be undertaken over a eight-month period with the potential to be hired by our client afterwards.

The resident will be reporting to an Amii Machine Learning Scientist and regularly consult with the Client team to share insights and engage in knowledge transfer activities. About our ClientZamplo is a digital health company transforming the way individuals, clinicians, and researchers engage with health data. Its connected health platform empowers people to track and share their own health information, while providing real-time insights that support better care and outcomes.

Zamplo develops innovative, patient-centered tools that reduce costs and improve collaboration across the healthcare system.The Zamplo platform offers two complementary products:Zamplo App: Allows patients to track symptoms, medications, routines, and share information with their care team. It helps patients better manage their health and prepare for meaningful conversations with providers.Zamplo Research: An electronic data capture platform designed for researchers, clinicians, and organizations. With patient consent it enables collection of patient-reported outcomes and wearable data, supports electronic consent, and streamlines data management to advance clinical research and improve care delivery.About the Project The project aims to use machine learning to classify a patient's risk of an adverse event leading to an emergency room visit following radiation therapy.

This risk assessment will use socio-demographic, non-medical and medical data. By identifying patients with a higher risk of an adverse event earlier, patients, healthcare providers, caregivers, and community stakeholders can implement proactive measures to improve patient outcomes.As research in this specific area is limited, the resident would approach the classification problem in a number of ways, each with its own set of experiments and models to determine the best option to implement. Following model development, the results will be externally validated in both retrospective and prospective manners.Required Skills / ExpertiseWe're looking for a talented and enthusiastic individual with solid knowledge of machine learning, experience working with health care data, and a passion to improve individual health outcomes.Key Responsibilities: Utilize a range of supervised, unsupervised methods to build a robust and deployable predictive model.

Ingest and understand (including performing exploratory data analysis and baseline statistical assessments) medical data from multiple patient health data sources. Experiment and fine-tune the model(s) as necessary based on the performance of baseline and deployment expectations. Collaborate with the project team and domain experts to iteratively develop models and define identified health event outcomes.

Implement model explainability and interpretability techniques to provide insights to patients and clinicians. Participate in regular meetings with the client and stakeholders, preparing presentations and reports. Research and implement different approaches to the problem from literature as well as publicly available tools.

Required Qualifications: Completion of a Computer Science (or a related graduate degree program) MSc. or PhD with specialization in predictive health or medical applications. Proficient in developing and training, fine-tuning and evaluating machine learning and deep neural network models in PyTorch and/or TensorFlow.

Proficient in Python programming language and related ML frameworks, libraries and toolkits. Solid understanding of classical statistics and its application in model validation. Familiarity with Linux, Git version control, and writing clean code.

A positive attitude towards learning and understanding a new applied domain . Must be a Permanent Resident or Canadian Citizen Preferred Qualifications: Familiarity with and hands-on experience with medical and/or health data. Experience with survival analysis and time-to-event modeling.

Publication record in peer-reviewed academic conferences or relevant journals in machine learning. Experience/familiarity with software engineering best practices. Experience using cloud platforms (GCP, AWS, Azure, etc.) Experience in using statistical tools such as SPSS, Stata etc.

Non-Technical Requirements: Desire to take ownership of a problem and demonstrate leadership skills. Interdisciplinary team player enthusiastic about working together to achieve excellence. Capable of critical and independent thought.

Able to communicate technical concepts clearly and advise on the application of machine intelligence. Intellectual curiosity and the desire to learn new things, techniques, and technologies. Why You Should ApplyBesides gaining industry experience, additional perks include: Work under the mentorship of an Amii Scientist for the duration of the project.

Participate in professional development activities. Gain access to the Amii community and events. Get paid for your work (a fair and equitable rate of pay will be negotiated at the time of offer).

Build your professional network. The opportunity for an ongoing machine learning role at the client's organization at the end of the term (at the client's discretion). Location: Alberta PreferredHow to ApplyIf this sounds like the opportunity you've been waiting for, please don't wait for the closing April 24, 2026 to apply - we're excited to add a new member to the Amii team for this role, and the posting may come down sooner than the closing date if we find the right candidate before the posting closes!

When sending your application, please send your resume and cover letter indicating why you think you'd be a fit for Amii. In your cover letter, please include one professional accomplishment you are most proud of and why.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.