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New Grad Machine Learning Jobs in Alberta (NOW HIRING)

DataVisor

Delivery Engineer - Canada

Calgary, AB · On-site

CA$80K - CA$120K/yr

Its patented unsupervised machine learning technology, advanced device intelligence, powerful ... Work closely with product and engineering teams to ensure seamless integration of new features and ...

HUB

Data Scientist

Edmonton, AB · On-site

You enjoy ambiguity, you pick up new tools quickly, and you care about outcomes more than orthodoxy ... Working knowledge of statistics, machine learning fundamentals, and model evaluation; able to ...

HUB

Data Scientist

Red Deer, AB · On-site

You enjoy ambiguity, you pick up new tools quickly, and you care about outcomes more than orthodoxy ... Working knowledge of statistics, machine learning fundamentals, and model evaluation; able to ...

Softchoice

Sr. AI Engineer

Calgary, AB · On-site

CA$91K - CA$114K/yr

AI or machine learning certifications (e.g., AI-900, AWS Certified Machine Learning Engineer ... Whether you are new to corporate tech, returning to work after a gap in employment, or looking to ...

Lifemark Health Group

Physiotherapist

Grande Prairie, AB · On-site

CA$46 - CA$51/hr

Team culture that values collaboration, learning, and shared success. * Centralized support so you can focus on care, not administration. * Robust onboarding and supervised new grad program.

SLB

Process Simulation Software Developer

Calgary, AB · On-site

You will also have opportunities to explore AI, machine learning, and data-driven techniques to ... Growth mindset and enthusiasm for learning new technologies. Must be legally authorized to work and ...

Canadian Natural

Recruitment Student

Calgary, AB · On-site

... learning. Building on classroom studies, you will develop and enhance your skills while working ... Students may be considered for permanent, full-time positions upon graduation through our New Grad ...

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All JobsNew Grad Machine Learning JobsNew Grad Machine Learning Jobs in Alberta

New Grad Machine Learning information

What is a new grad machine learning?

New Grad Machine Learning roles are entry-level positions designed for recent graduates who have studied machine learning, artificial intelligence, data science, or related fields. These positions typically involve working with experienced data scientists and engineers to develop, implement, and improve machine learning models and algorithms. New grads in these roles often contribute to projects involving data preprocessing, model training, evaluation, and deployment. The goal is to help new graduates gain hands-on experience and grow their skills in a real-world setting while contributing to the organization's AI initiatives.

What skills and qualifications are needed to thrive as a new grad machine learning?

To thrive as a New Grad Machine Learning Engineer, you need a solid foundation in mathematics, statistics, and programming (especially Python), typically supported by a degree in computer science or a related field. Familiarity with machine learning frameworks such as TensorFlow or PyTorch, version control systems like Git, and coursework or certification in data science are highly beneficial. Strong problem-solving abilities, curiosity, and effective communication skills help you collaborate and convey complex technical concepts to diverse teams. These skills and qualities are essential for developing innovative models, ensuring project success, and integrating seamlessly into fast-paced tech environments.

What challenges do new graduates face when starting out in a machine learning role, and how can they overcome them?

New grad machine learning engineers often encounter challenges such as bridging the gap between academic knowledge and practical, production-level projects. Adapting to real-world data issues, collaborating with cross-functional teams, and understanding scalable deployment can be daunting at first. To overcome these, it's helpful to seek mentorship, proactively ask questions, and dedicate time to learning best practices in code versioning, model evaluation, and team communication. Engaging in code reviews and participating in team discussions can also accelerate the learning curve and foster professional growth.

What is the difference between New Grad Machine Learning vs Data Scientist?

AspectNew Grad Machine LearningData Scientist
Required CredentialsBachelor's in CS, Data Science, or related field; some internshipsBachelor's or Master's in CS, Statistics, or related; some experience
Work EnvironmentEntry-level, team-focused, research and developmentData analysis, modeling, cross-functional collaboration
Employer & Industry UsageTech companies, startups, research labsTech, finance, healthcare, consulting firms

New Grad Machine Learning roles typically focus on foundational skills, internships, and entry-level tasks, while Data Scientist positions often require more experience in data analysis and statistical modeling. Both roles are common in tech industries, but Data Scientists usually handle broader data analysis responsibilities.

What are popular job titles related to New Grad Machine Learning jobs in Alberta?

For New Grad Machine Learning jobs in Alberta, the most frequently searched job titles are:

What job categories do people searching New Grad Machine Learning jobs in Alberta look for?

The top searched job categories for New Grad Machine Learning jobs in Alberta are:

New Grad Machine Learning jobs near you
Infographic showing various New Grad Machine Learning job openings in Alberta as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 73% Full Time, 22% Part Time, and 3% Contract. Highlights an 82% Physical, 3% Hybrid, and 15% Remote job distribution.

Delivery Engineer - Canada

Calgary, AB • On-site

DataVisor
Software Development • 1 - 10 employees
Learn more about DataVisorexternal

CA$80K - CA$120K/yr

Full-time

Medical, PTO

Re-posted 11 days ago

Job description

DataVisor is the world's leading AI-powered Fraud and Risk Platform that delivers the best overall detection coverage in industry. With an open SaaS platform that supports easy consolidation and enrichment of any data, DataVisor's solution scales infinitely and enables organizations to act on fast-evolving fraud and money laundering activities in real time. Its patented unsupervised machine learning technology, advanced device intelligence, powerful decision engine and investigation tools work together to provide guaranteed performance lift from day one. DataVisor's platform is architected to support multiple use cases across different business units flexibly, dramatically lowering total cost of ownership, compared to legacy point solutions. DataVisor is recognized as an industry leader and has been adopted by many Fortune 500 companies across the globe.

Our award-winning software platform is powered by a team of world-class experts in big data, machine learning, security, and scalable infrastructure. Our culture is open, positive, collaborative, and results-driven. Come join us!

Position Overview:

We are seeking a Delivery Engineer to join our Delivery team. The ideal candidate will lead client communications and drive end-to-end project delivery, while designing and implementing innovative integration solutions that meet both technical and business requirements.This role requires close collaboration with clients, sales teams, and internal stakeholders to ensure successful project outcomes. As a technical delivery leader, the TPM will own and manage all engineering work streams, coordinating across teams to keep projects on schedule and aligned with scope. The role is hands-on, requiring the ability to contribute directly to technical implementation and problem-solving as needed.

Key Responsibilities:

  • Manage and drive client communications throughout the entire project delivery, align different client stakeholders, ensure project is delivered successfully without delay.
  • Work closely with clients, sales teams, and other stakeholders to ensure successful project outcomes.
  • Understand the client's product and business logic to recommend the best solution that addresses specific client needs. Provide strong solution and consulting services.
  • Take the project management role to ensure the client onboarding project runs as expected and under control.
  • Provide technical expertise and guidance throughout the implementation and deployment phases, to integrate with the client systems.
  • Work closely with product and engineering teams to ensure seamless integration of new features and technologies into existing systems.
  • Stay updated on financial services industry trends and emerging technologies to continuously improve our solutions and offerings.
  • Conduct presentations and demonstrations of proposed solutions to clients and stakeholders.

Requirements

Qualifications:

  • Bachelor's degree in Computer Science, Engineering or a related field is required; a Master's degree in a business-related discipline (e.g., MBA, MIS, Information Systems, Management, or Analytics) is preferred.
  • Basic understanding of software development, system architecture, and system integration concepts; exposure to SaaS platform data integration is a plus.
  • Strong verbal and written communication skills, with the ability to clearly explain technical concepts to both technical and non-technical audiences.
  • Enjoys working with clients and stakeholders, with a service-oriented mindset and interest in client-facing responsibilities.
  • Ability to work collaboratively in a team environment and support multiple projects under guidance and supervision.
  • Demonstrates strong problem-solving skills, attention to detail, and a willingness to learn in a fast-paced environment.
  • Familiarity with anti-fraud concepts in the financial services or internet industry is a plus.
  • Exposure to real-time computing, big data technologies, or machine learning through coursework, internships, or project experience is a plus.

Benefits

1. Health Insurance, PTO, stock option

2. The expected salary range for this role is CAD $80,000 - $120,000 per year, depending on experience, qualifications, and location. Final compensation will be determined based on job-related skills and business needs

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