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Senior Machine Learning Engineer Jobs in British Columbia

Vancity

Senior Machine Learning Engineer

Vancouver, BC · Remote

As a Senior Machine Learning Engineer, you will join our Data Science & AI Pod, focused on designing, building, and deploying enterprise-wide AI and machine learning solutions that support business ...

Weir

Senior Machine Learning Developer

Vancouver, BC · Hybrid

Senior Machine Learning Developer Vancouver - Hybrid Job Summary Shape the future of AI in mining by developing production-ready machine learning solutions that drive safer, smarter and more ...

New

Clio

Machine Learning Engineer

Vancouver, BC · Hybrid

CA$152K - CA$174K/yr

We are currently seeking a Machine Learning Engineer to join our rapidly growing engineering team. This role is for someone who is passionate about building innovative solutions and being exposed to ...

MetaOptima

Machine Learning Engineer

Vancouver, BC · On-site

$100 - $140/hr

As a Machine Learning Engineer, you will join a small, high-impact R&D team and own the full ML lifecycle -- from research and rapid prototyping through data pipelines, model training, and cloud ...

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All JobsMachine Learning Engineer JobsSenior Machine Learning Engineer JobsSenior Machine Learning Engineer Jobs in British Columbia

Senior Machine Learning Engineer information

See British Columbia salary details

$45K

$165.3K

$248.5K

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

As of Jul 29, 2026, the average yearly pay for senior machine learning engineer in British Columbia is $165,321.00, according to ZipRecruiter salary data. Most workers in this role earn between $137,500.00 and $184,000.00 per year, depending on experience, location, and employer.

What are some common challenges Senior Machine Learning Engineers face when deploying models to production, and how can they be addressed?

Senior Machine Learning Engineers often encounter challenges related to model scalability, maintaining performance in real-world scenarios, and ensuring reliable integration with existing systems. Addressing these challenges typically involves thorough testing, implementing robust monitoring for model drift, and collaborating closely with DevOps and software engineering teams to streamline deployment pipelines. Staying updated on best practices in MLOps and adopting tools for automated deployment and monitoring can greatly improve the reliability and efficiency of production models.

What does a Senior Machine Learning Engineer do?

A Senior Machine Learning Engineer designs, develops, and implements machine learning models to solve complex problems. They are responsible for selecting appropriate algorithms, preprocessing data, and optimizing model performance. Additionally, they collaborate with data scientists, software engineers, and product teams to integrate machine learning solutions into production systems. Senior engineers also mentor junior team members and contribute to setting technical direction for machine learning projects.

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

To thrive as a Senior Machine Learning Engineer, you need advanced knowledge of machine learning algorithms, statistical modeling, and programming languages like Python or Java, typically supported by a degree in computer science or a related field. Experience with frameworks and tools such as TensorFlow, PyTorch, scikit-learn, and cloud platforms, as well as familiarity with version control and CI/CD systems, is essential. Strong problem-solving, communication, and leadership skills help you collaborate effectively and mentor junior team members. These capabilities are crucial for designing scalable ML solutions and driving impactful results within complex, dynamic projects.

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

AspectSenior Machine Learning EngineerData Scientist
Required CredentialsBachelor's/Master's in CS, ML, or related; experience with ML frameworksBachelor's/Master's in CS, Statistics, or related; strong analytical skills
Work EnvironmentDevelops and deploys ML models in production systemsAnalyzes data, builds models, and provides insights
Industry UsageTech, finance, healthcare, e-commerceResearch, finance, marketing, tech

While both roles require strong technical skills and knowledge of machine learning, Senior Machine Learning Engineers focus more on deploying scalable ML solutions in production environments, whereas Data Scientists primarily analyze data and develop models for insights. The roles often overlap but differ in their core responsibilities and focus areas.

What are the most commonly searched types of Machine Learning Engineer jobs in British Columbia? The most popular types of Machine Learning Engineer jobs in British Columbia are:
What are popular job titles related to Senior Machine Learning Engineer jobs in British Columbia? For Senior Machine Learning Engineer jobs in British Columbia, the most frequently searched job titles are:
What job categories do people searching Senior Machine Learning Engineer jobs in British Columbia look for? The top searched job categories for Senior Machine Learning Engineer jobs in British Columbia are:
What cities in British Columbia are hiring for Senior Machine Learning Engineer jobs? Cities in British Columbia with the most Senior Machine Learning Engineer job openings:
Senior Machine Learning Engineer jobs near you
Infographic showing various Senior Machine Learning Engineer job openings in British Columbia as of July 2026, with employment types broken down into 93% Full Time, 4% Part Time, and 3% Contract. Highlights an 86% Physical, 5% Hybrid, and 9% Remote job distribution, with an average salary of $165,321 per year, or $79.5 per hour.

Senior Machine Learning Engineer

Starboard Recruitment

Vancouver, BC

$150K - $170K/yr

Full-time

Re-posted 10 days ago

Job description

Follow Starboard Recruitment on LinkedIn for ongoing job opportunities, market updates and advice: https://www.linkedin.com/company/starboard-recruitment
Opportunity is with one of Canada's fastest growing, well-funded, Series-B tech startups in the AI / ML domain.
Starboard Recruitment, on behalf of our client, is searching for an experienced Sr Machine Learning Engineer.
Our team will reach out to qualified candidates and discuss in further detail.
Key Responsibilities

  • AI Strategy Development – Partner with the Director of R&D to define and execute the company’s AI strategy, focusing on geoscientific applications.

  • Full-Cycle ML Leadership – Manage all aspects of the machine learning lifecycle, from data preprocessing to model deployment and performance monitoring, ensuring a streamlined and effective process.

  • Innovative ML Architectures – Design and implement a broad spectrum of machine learning solutions, spanning computer vision, time series forecasting, and geospatial data analysis, while integrating cutting-edge technologies and methodologies.

  • MLOps Best Practices – Drive the adoption of robust MLOps frameworks, including CI/CD pipelines for ML models, to enable smooth and scalable AI deployments.

  • AI Infrastructure & Optimization – Enhance AI infrastructure and workflows, focusing on performance, scalability, data pipeline efficiency, and automation across all ML processes.

  • Cross-Disciplinary Collaboration – Work closely with data engineers, scientists, and geoscientists to establish a well-integrated, end-to-end ML ecosystem within the company.

  • Continuous AI Advancement – Regularly improve the efficiency, reliability, and impact of AI-driven systems through iterative optimizations and refinements.

  • Geospatial ML Expertise – Familiarity with geospatial databases such as PostGIS and GeoPandas is highly desirable.

Qualifications

Experience:

  • At least 7 years of hands-on experience in machine learning engineering, with a strong record of successfully deploying ML solutions into production environments.

Technical Proficiency:

  • Expert-level Python programming skills and deep knowledge of ML frameworks, including PyTorch, scikit-learn, and inference engines like ONNX Runtime and OpenVINO.

  • Strong grasp of various ML algorithms, architectures, and their real-world applications.

  • Experience working with large-scale datasets and cloud computing environments, particularly AWS.

  • Proficiency in software engineering best practices, version control systems, and CI/CD methodologies.

  • Hands-on experience with containerization, orchestration, and microservices-based architectures.

  • Solid understanding of data security, privacy considerations, and compliance requirements in AI-driven applications.

Leadership & Soft Skills:

  • Proven ability to lead and mentor ML teams through complex projects.

  • Strong analytical and strategic thinking skills to solve challenging AI problems.

  • Exceptional communication skills, capable of conveying technical concepts to both technical teams and executive stakeholders.

  • Strong project management capabilities, with the ability to oversee multiple initiatives simultaneously.

  • Passion for continuous learning and adaptability in the ever-evolving field of machine learning.

Education:

  • Master’s or Ph.D. in Computer Science, Machine Learning, or a related discipline. Industry certifications and contributions to the ML community (such as research publications or open-source projects) are a strong plus.

Follow Starboard Recruitment on LinkedIn for ongoing job opportunities, market updates and advice: https://www.linkedin.com/company/starboard-recruitment