Machine Learning, Huawei jobs in Vancouver, BC
- Armstrong CollectiveVancouver, BC
- $125,000–$145,000 a year
- Permanent
- Vision care
- Dental care
- Life insurance
- Disability insurance
- RRSP match
- 5+ years of hands on experience in machine learning engineering or a closely related role, including significant experience deploying ML systems into production…
- Amazon Development Centre Canada ULCVancouver, BC
- $114,800–$191,800 a year
- Full-time
- Paid time off
- Vision care
- Dental care
- Profit sharing
- RRSP
- Bachelor's degree in computer science or equivalent.
- Experience with full-stack development, distributed systems, agentic AI and machine learning will be…
- Brock SolutionsVancouver, BC
- $65,000–$90,000 a year
- On call
- Profit sharing
- Company events
- Extended health care
- Flexible schedule
- Bachelor degree in Electrical Engineering, Mechatronics, Systems design, Automation, Industrial Engineering or College equivalent.
- A.H. Lundberg Systems LimitedVancouver, BC V5R 4H1
- $43.27 an hour
- Vision care
- Dental care
- Extended health care
- Design power plants, machines and equipment.
- Investigate mechanical failures or unexpected maintenance problems.
- Hours: 40 hours per week.
Machine Learning Engineer (Energy) - MLEEAS
Easily applyOften replies in 5 daysNavitasPartnersVancouver, BC- From $30 an hour
- The ML Engineer will develop and deploy machine learning models supporting predictive maintenance, energy demand forecasting, asset optimization, and renewable…
Machine Learning Engineer (BFSI) - MLEBAS
Easily applyOften replies in 5 daysNavitasPartnersVancouver, BC- From $30 an hour
- Develop machine learning models and pipelines.
- 5+ years of machine learning experience.
- Bachelor's or Master's degree in Data Science, AI, Computer Science, or…
- Amazon Development Centre Canada ULCVancouver, BC
- $278,500–$465,100 a year
- Full-time
- Experience working with big data, machine learning and predictive modeling.
- Experience building large-scale machine learning and AI solutions at Internet scale.
- Amazon Development Centre Canada ULCVancouver, BC
- $278,500–$465,100 a year
- Full-time
- Experience working with big data, machine learning and predictive modeling.
- Experience building large-scale machine learning and AI solutions at Internet scale.
Manager, MLOps and Platform Infrastructure
Easily applyTorus Talent Consultants LTDVancouver, BC- $160,000–$200,000 a year
- Our client, is a research-driven technology company building advanced data-intensive systems that combine proprietary hardware with large-scale machine learning…
- Wolf Advanced TechnologyBritish Columbia
- $120,000–$150,000 a year
- Full-time
- Paid time off
- Relocation assistance
- Disability insurance
- Profit sharing
- Paid vacation
- To join our pack, applicants must be able to provide valid documentation to show Canadian or US citizenship or Canadian Permanent Residency and undergo a police…
AI Software Engineer
Easily applyAlexander CollegeVancouver, BC- $100,000 a year
- Full-time +1
- Monday to Friday +2
- Paid time off
- Vision care
- Dental care
- Company events
- Extended health care
- On-site parking
- Solid machine learning and deep learning foundations, including linear algebra, calculus, loss design, batch training, efficient fine-tuning, offline training,…
Full Stack Developer (AI-Enabled)
Easily applyAlexander CollegeVancouver, BC- $70,000–$80,000 a year
- Full-time +1
- Paid time off
- Vision care
- Dental care
- Company events
- Extended health care
- On-site parking
- Bachelor’s or Master's degree in a related field preferred.
- Vancouver, BC: reliably commute or plan to relocate before starting work (required).
MLOps Engineer (Energy) - MLEAS
Easily applyOften replies in 5 daysNavitasPartnersVancouver, BC- From $30 an hour
- 5+ years in MLOps or ML Platform Engineering.
- The MLOps Engineer will establish and manage scalable ML infrastructure, ensuring efficient deployment, monitoring…
MLOps Engineer (BFSI) - MLEBAS
Easily applyOften replies in 5 daysNavitasPartnersVancouver, BC- From $30 an hour
- Implement CI/CD for machine learning workloads.
- The MLOps Engineer will establish scalable machine learning operations frameworks and automate the deployment,…
- View all NavitasPartners jobs - Vancouver jobs - Engineer jobs in Vancouver, BC
- Salary Search: MLOps Engineer (BFSI) - MLEBAS salaries in Vancouver, BC
- WSPVancouver, BC
- $73,000–$101,500 a year
- Registration or eligibility for registration as a Professional Engineer or Geoscientist with EGBC.
- Advanced degree (MSc or PhD) in Geology, Environmental…
- View all WSP jobs - Vancouver jobs - Hydrogeologist jobs in Vancouver, BC
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- See popular questions & answers about WSP
- Best BuyVancouver, BC
- $95,000–$105,000 a year
- Full-time
- Wellness program
- Experience breaking down complex business problems into actionable data solutions using statistical methods, modeling, or machine learning.
- View all Best Buy jobs - Vancouver jobs
- Salary Search: Senior Data Analyst salaries in Vancouver, BC
- See popular questions & answers about Best Buy
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Job Post Details
AI/Machine Learning Engineer - job post
Job details
Pay
- $125,000–$145,000 a year
Job type
- Permanent
Location
Benefits
Pulled from the full job description
- Vision care
- Dental care
- Life insurance
- Disability insurance
- RRSP match
Full job description
Purpose
Reporting to Director, Data, the AI and Machine Learning Engineer is responsible for designing, building, and operating production grade machine learning systems that deliver measurable business outcomes. This is a senior individual contributor role requiring strong technical judgment, end to end ownership, and the ability to translate complex business problems into reliable, scalable AI solutions.
The role partners closely with data engineering, software development, product, and business stakeholders while remaining accountable for the quality, performance, and sustainability of deployed ML systems.
Key Responsibilities
- Design, develop, and deploy scalable machine learning models and AI systems across multiple business domains, including dynamic pricing, revenue management, forecasting, classification, recommendation systems, and natural language processing
- Own the full machine learning lifecycle, from problem definition and data exploration through model training, evaluation, deployment, monitoring, and iteration in production
- Build and productionize pricing and revenue models that balance revenue, margin, conversion, and regulatory constraints, ensuring models operate safely and reliably in live environments
- Partner with data engineers to design and maintain robust data pipelines that support machine learning systems with high quality, reliable data inputs
- Collaborate with product, pricing, and business stakeholders to translate requirements into technical solutions with clearly defined success metrics tied to business outcomes
- Design and execute experiments (e.g., A/B tests, causal inference, bandits) to evaluate real world impact and inform model improvements beyond offline performance metrics
- Ensure strong model governance practices, including documentation, versioning, monitoring, and compliance with enterprise and regulatory standards
- Monitor deployed models for performance degradation, bias, and drift, and implement retraining or mitigation strategies as required
- Contribute to the evaluation and responsible adoption of emerging AI/ML techniques, tools, and platforms, including generative AI and foundation models
- Provide technical mentorship, code reviews, and knowledge sharing to support team capability and engineering excellence, without direct people management accountability
What You Bring
- Strong ownership mindset with accountability for delivering high quality, production ready ML systems
- Ability to communicate complex technical concepts clearly to both technical and non technical audiences
- Sound technical judgment when making trade offs between model performance, scalability, risk, and business impact
- Curiosity and adaptability in exploring new techniques, tools, and approaches
- Resilience and persistence when solving ambiguous, high impact problems
Experience & Qualifications
- 5+ years of hands on experience in machine learning engineering or a closely related role, including significant experience deploying ML systems into production environments
- Strong proficiency in Python and modern ML frameworks and libraries (e.g., scikit learn, PyTorch, TensorFlow, gradient boosting frameworks)
- Experience deploying and operating ML models in cloud environments (AWS, Azure, or GCP), including containerization and model serving
- Solid understanding of MLOps practices, including CI/CD for ML, model versioning, monitoring, and experiment tracking
- Strong foundation in statistics, experimental design, and model evaluation
- Experience with generative AI, LLMs, or agent based frameworks considered an asset
Work Environment
- Eligible to work in Canada
- Hybrid working arrangements with 3 days work from office
Compensation
- The base salary offered for this role is $125,000 to $145,000 per annum and can vary based on job-related expertise, qualifications, experience and internal equity.
- Eligible for Armstrong Collective’s discretionary bonus program
Eligible Benefits
Armstrong Collective supports our team members’ health and wellness by providing a comprehensive medical plan with 100% employer paid premiums, some of which includes:
- Medical, Dental, Vision, Life Insurance
- Short term disability, long term disability benefits
- Travel emergency assistance
- Vacation time and sick time
- Up to 5% RRSP and/or TSFA match
- Two complimentary annual train tickets after first year of employment
Armstrong Collective, Rocky Mountaineer and Canyon Spirit are an equal opportunity employer, driven by our values of creating meaningful moments, being one team, and achieving extraordinary outcomes. Our strong company culture supports our vision of a diverse, open, safe, and respectful workplace. We celebrate diversity and are committed to creating an inclusive environment for all team members. If you require any accommodation during the application process or throughout your employment, please let us know. We will work with you to ensure your needs are met and to create a supportive environment.
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