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Scientific Machine Learning Jobs in British Columbia

Remitly

Senior Machine Learning Engineer

Burnaby, BC · On-site

CA$168K - CA$210K/yr

Partner with data scientists, product owners, and engineers across verticals to turn prototypes ... Machine Learning systems in production. * Strong programming skills in Python, Go, Scala or a ...

Teck

Data Scientist III

Vancouver, BC · Hybrid

CA$107K - CA$132K/yr

Design, develop, and deploy machine learning models, advanced analytics, and Generative AI ... Master's or PhD in Data Science, Computer Science, Statistics, or a related quantitative field ...

Dialpad

Applied Scientist

Vancouver, BC · On-site +1

... scientific community by reviewing submissions. Skills you'll bring * Master's or PhD degree in Linguistics, Computational Linguistics, Computer Science, Machine Learning, or related fields. * 2+ ...

Clio

Manager, Machine Learning Engineering

Vancouver, BC · Remote

CA$181K - CA$272K/yr

We are currently seeking a Manager, Machine Learning Engineering to join our rapidly growing ... science to identify new tooling for ML and LLM-driven features for Clio customers. * Work in an ...

Gibraltar Mine

Data Scientist

Mcleese Lake, BC

CA$102K - CA$128K/yr

Position Title Data Scientist, Technical Services Employment Type Full-Time Organization Gibraltar ... Gibraltar Mine currently uses machine learning tools in our milling processes. This role's key ...

MasterCard

Director, Data Science

Vancouver, BC

Title and Summary Director, Data Science Overview The Security Solutions Data Science team is responsible for delivering Artificial Intelligence (AI) and Machine Learning (ML) models that support ...

MasterCard

Lead Data Scientist

Vancouver, BC · Hybrid

The Data Science team is responsible for developing advanced AI and machine learning solutions that power critical products across Mastercard's network. This role will support the merchant/acquiring ...

MasterCard

Data Scientist II

Vancouver, BC

Title and Summary Data Scientist II Overview The Security Solutions Data Science team is responsible for developing Artificial Intelligence (AI) and Machine Learning (ML) models that power Mastercard ...

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Showing results 21-40

All JobsScientific Machine Learning JobsScientific Machine Learning Jobs in British Columbia

Scientific Machine Learning information

What is scientific machine learning?

Scientific machine learning (SciML) is an interdisciplinary field that combines principles from machine learning and scientific computing to solve complex scientific and engineering problems. It involves developing algorithms and models that can learn from data and physical laws, such as differential equations, to make predictions, optimize systems, or gain insights into phenomena. SciML is widely used in areas like physics, biology, climate science, and engineering, enabling researchers to accelerate simulations and make data-driven discoveries. The field often leverages both traditional numerical methods and modern machine learning techniques, making it a rapidly evolving area of research.

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

To thrive as a Scientific Machine Learning professional, you need a strong background in mathematics, statistics, programming (often Python), and domain-specific scientific knowledge, typically with a graduate degree in a STEM field. Proficiency in machine learning frameworks (such as TensorFlow or PyTorch), scientific computing tools (like NumPy, SciPy), and experience with high-performance computing are commonly required. Critical thinking, problem-solving, and collaborative communication are vital soft skills for designing experiments and interpreting complex data. These skills ensure robust, reproducible results and the ability to bridge scientific inquiry with advanced computational methods.

What are some common challenges faced by professionals in scientific machine learning, and how can they be addressed?

Professionals in Scientific Machine Learning often encounter challenges such as integrating domain-specific scientific knowledge with machine learning models, managing large and complex datasets, and ensuring that models are interpretable and physically consistent. Collaboration with domain experts and interdisciplinary teams is essential to bridge knowledge gaps and validate results. To address these challenges, it is helpful to invest time in understanding the underlying scientific principles, keep up-to-date with advancements in both machine learning and scientific fields, and utilize specialized tools and frameworks designed for scientific data.

What is the difference between Scientific Machine Learning vs Data Scientist?

AspectScientific Machine LearningData Scientist
Required credentialsAdvanced degrees in CS, ML, or related fields; knowledge of scientific computingDegree in CS, statistics, or related fields; strong analytical skills
Work environmentResearch labs, academia, industry R&D teamsBusiness analytics, tech companies, consulting firms
Industry usageResearch, scientific computing, engineering simulationsBusiness insights, predictive modeling, data analysis

Scientific Machine Learning focuses on integrating scientific knowledge with machine learning techniques for research and engineering applications. Data Scientists analyze data to extract insights and build predictive models for business or operational purposes. While both roles require strong technical skills, Scientific Machine Learning emphasizes scientific computing and domain-specific modeling, whereas Data Scientists focus on data analysis and visualization.

What are popular job titles related to Scientific Machine Learning jobs in British Columbia?

For Scientific Machine Learning jobs in British Columbia, the most frequently searched job titles are:

What job categories do people searching Scientific Machine Learning jobs in British Columbia look for?

The top searched job categories for Scientific Machine Learning jobs in British Columbia are:

Scientific Machine Learning jobs near you
Infographic showing various Scientific Machine Learning job openings in British Columbia as of August 2026, with employment types broken down into 1% As Needed, 68% Full Time, 30% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Senior Machine Learning Engineer

Remitly

Burnaby, BC • On-site

CA$168K - CA$210K/yr

Full-time

Medical, Life, Retirement, PTO

Posted 6 days ago

Job description

Job Description:

At Remitly, we believe everyone deserves the freedom to access, move, and manage their money wherever life takes them. Since 2011, we've tirelessly delivered on our promise to customers sending money globally, providing secure, simple, and reliable ways to manage their money, ensuring true peace of mind. Whether it's supporting loved ones back home, growing a business across continents, or pursuing new opportunities abroad, we're not just here to move money- we're here to move our global customers forward.
We're looking for builders, reimaginers, and global thinkers who want to work at the intersection of technology, trust, and transformation. If that's you and you're ready to do the most meaningful work of your career-we invite you to join over 2,800 passionate Remitlians worldwide who are united by our vision to transform lives with trusted financial services that transcend borders.

About the Role:

As a Senior Machine Learning Engineer in Remitly's Core AI/ML team, you'll work at the heart of our AI strategy. The Core AI/ML team is responsible for building the foundational machine learning systems, frameworks, and services that power Remitly's next generation of products and operations. We work horizontally across domains at Remitly-Global Money Movement, Treasury, Identity & Trust, Promotions, Referrals, etc.

We are looking for an experienced Machine Learning Engineer to build large scale systems that propel our next phase of growth.

You Will:

  • Lead the end-to-end ML lifecycle from raw data to EDA to model training to offline/online evaluation and model deployment.
  • Design, build, and scale feature pipelines for batch and real-time ML applications.
  • Partner with data scientists, product owners, and engineers across verticals to turn prototypes into reliable, customer-facing ML systems.
  • Optimize models and pipelines using MLOps best practices: automated retraining, drift detection, CI/CD, monitoring, observability.
  • Mentor and lead other engineers: champion design reviews, technical discussions, and maintain a high bar code quality.

You Have:

  • Degree in Computer Science, Data Science, Statistics, Mathematics or equivalent practical experience.
  • 8+ years delivering Machine Learning systems in production.
  • Strong programming skills in Python, Go, Scala or a similar language.
  • Hands-on experience with ML frameworks (e.g., PyTorch, scikit-learn, numpy).
  • Experience working with major cloud platforms (AWS, GCP, or Azure).
  • Experience with one or more of Deep Learning algorithms, Large Language Models, Casual Inference, Personalization, Knowledge Graphs, Natural Language Processing would be desirable.

Compensation Details. The starting base salary range for this position is $168,000-$210,000. In Canada, Remitly employees are shareholders in our Company and equity is part of our total compensation plan. Your recruiter can share more information about medical benefits offered, as well as other financial benefits and total compensation components offered with this role.

Our Benefits

  • Four weeks vacation
  • Health Benefits
  • Mental Health & Family Forming Benefits
  • RRSP plan with company match
  • Employee Stock Purchase Plan (ESPP)
  • Life Insurance & Disability
  • Continuing education

Our Connected Work Culture: Driving Innovation, Together

At Remitly, we believe that true innovation sparks when we come together. Our Connected Work Culture fosters dynamic in-person collaboration, where ideas ignite and challenging problems find solutions faster. For corporate team members, we have an in-office expectation of at least 50% of the time monthly, typically achieved by coming in three days a week. This creates a consistent, meaningful overlap that supports team norms and business needs. Managers also have the flexibility to set higher expectations based on their team's specific needs. These intentional in-office moments are vital for deepening relationships, fueling creativity, and ensuring your impact is felt where it matters most.

Remitly is an E-Verify Employer

At Remitly, we are dedicated to ensuring that our workplace offers equal employment opportunities to all employees and candidates, in full compliance with applicable laws and regulations.

Remitly is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

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