Machine operator • vancouver bc
Architect & Build: Design, develop, and deploy scalable machine learning models and AI systems (ranging from predictive models to Generative AI and LLM-powered agents) that directly impact Workday'... Voir plus
And more than ever, it’s our future.A future where we’re always looking forward.Always serving up new ways to meet life’s moments.A future where we keep dreaming bigger.We look for people with pass... Voir plus
Education: Secondary (high) school graduation certificate.Experience: 2 years to less than 3 years.Operate mobile and tower cranes to lift, move, position or place equipment and materials.Perform p... Voir plus
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Love football (soccer) and have an entrepreneurial mindset?.Stranger Soccer is expanding across key cities worldwide and is seeking a License Owner to launch and grow the Stranger Soccer operation ... Voir plus
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As a Machine Learning Engineer, you'll design and implement scalable, high-performance machine learning systems to support DeviantArt's vibrant online community.You'll play a key role in building i... Voir plus
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Machine shop Helper – Aerospace Machine Shop.Entry Level | Long-Term Opportunity.We are looking for machine shop helper to join our growing aerospace machining team.We are seeking a handyman with b... Voir plus
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Are you looking for a new opportunity in a dynamic and supportive work environment? We are seeking motivated individuals to join our milling crew as Milling Operators for BA Blacktop Group of Compa... Voir plus
About the Role
What you will do:
Architect & Build: Design, develop, and deploy scalable machine learning models and AI systems (ranging from predictive models to Generative AI and LLM-powered agents) that directly impact Workday's core enterprise applications.
End-to-End Ownership: Take full ownership of the ML lifecycle, including data extraction, feature engineering, model training, deployment, optimization, and continuous monitoring in a high-scale production environment.
Cross-Functional Collaboration: Partner closely with Data Scientists, Software Engineers, Product Managers, and UX Designers to translate complex business problems into robust AI solutions.
Drive Technical Excellence: Establish and advocate for engineering best practices, robust MLOps processes, and highly optimized code.
Mentorship & Leadership: Guide and mentor junior engineers, conduct code and architecture reviews, and help shape the technical roadmap for your team.
Champion Responsible AI: Ensure all models adhere to Workday's strict standards for data privacy, security, fairness, and ethical AI practices.
About You
Basic Qualifications (Sr Machine Learning Engineer)
Experience: 7+ years of industry experience in software engineering with a strong focus on applied machine learning, deep learning, or NLP.
Programming Mastery: Expert-level proficiency in Python and strong software engineering fundamentals (data structures, algorithms, object-oriented design).
ML Frameworks: Deep hands-on experience with industry-standard machine learning and deep learning libraries (e.g., PyTorch, TensorFlow, Scikit-learn, Hugging Face).
Production Deployment: Proven track record of taking ML models out of research/notebook environments and deploying them into scalable, high-traffic production systems.
Cloud & Infrastructure: Solid experience with cloud computing platforms (AWS or GCP) and modern infrastructure tools (Docker, Kubernetes).
Education: Bachelor's or Master's degree in Computer Science, Mathematics, Statistics, or a related highly quantitative field (or equivalent practical experience).
Basic Qualifications (Machine Learning Engineer)
Experience: 5+ years of industry experience in software engineering with a strong focus on applied machine learning, deep learning, or NLP.
Programming Mastery: Expert-level proficiency in Python and strong software engineering fundamentals (data structures, algorithms, object-oriented design).
ML Frameworks: Deep hands-on experience with industry-standard machine learning and deep learning libraries (e.g., PyTorch, TensorFlow, Scikit-learn, Hugging Face).
Production Deployment: Proven track record of taking ML models out of research/notebook environments and deploying them into scalable, high-traffic production systems.
Cloud & Infrastructure: Solid experience with cloud computing platforms (AWS or GCP) and modern infrastructure tools (Docker, Kubernetes).
Education: Bachelor's or Master's degree in Computer Science, Mathematics, Statistics, or a related highly quantitative field (or equivalent practical experience).
Workday Pay Transparency Statement
The annualized base salary ranges for the primary location and any additional locations are listed below. Workday pay ranges vary based on work location. As a part of the total compensation package, this role may be eligible for the Workday Bonus Plan or a role-specific commission/bonus, as well as annual refresh stock grants. Recruiters can share more detail during the hiring process. Each candidate’s compensation offer will be based on multiple factors including, but not limited to, geography, experience, skills, job duties, and business need, among other things. For more information regarding Workday’s comprehensive benefits, please .
Primary Location: CAN.BC.VancouverPrimary CAN Base Pay Range: $156,000 - $234,000 CADAdditional CAN Location(s) Base Pay Range: $156,000 - $234,000 CAD
