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Machine Learning Engineer II - Job Opportunity at Microsoft

Vancouver, Canada
Full-time
Mid-level
Posted: February 7, 2025
On-site
CAD 83,600 - 159,600 per year

Benefits

Comprehensive healthcare coverage with industry-leading options
Microsoft employee stock purchase program
Professional development and learning resources
Competitive paid time off and parental leave
Access to cutting-edge AI technologies and research

Key Responsibilities

Architect and develop next-generation AI evaluation platforms with enterprise-scale impact
Lead end-to-end ML pipeline design spanning training, analysis, and model serving
Drive implementation of state-of-the-art evaluation methodologies
Shape product features and evaluation metrics for Azure AI services
Collaborate with cross-functional teams to advance AI capabilities

Requirements

Education

Bachelor's Degree in Computer Science or related technical field

Experience

2+ years technical engineering experience

Required Skills

Python programming (2+ years) Machine learning Natural language processing Deep learning Reinforcement learning C, C++, C#, Java, JavaScript (proficiency in one or more)

Certifications

Microsoft Cloud Background Check
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Sauge AI Market Intelligence

Industry Trends

Rapid expansion of enterprise AI evaluation platforms as organizations scale their ML operations Growing demand for robust model evaluation frameworks due to increasing AI regulation and safety concerns Shift towards specialized AI infrastructure teams within major tech companies Rising importance of MLOps and evaluation metrics in production AI systems

Salary Evaluation

The offered range is competitive for Vancouver's market, with similar roles at major tech companies offering CAD 90,000 - 170,000. The wide range suggests significant room for negotiation based on experience.

Role Significance

Typically part of a 5-8 person specialized AI infrastructure team within the larger Azure AI organization
Mid-level individual contributor role with significant technical ownership and potential for architectural influence

Key Projects

Large-scale AI model evaluation systems MLOps pipeline development Platform architecture design Performance optimization for enterprise-scale AI workloads

Success Factors

Deep technical expertise in ML systems and evaluation methodologies Ability to balance theoretical ML knowledge with practical engineering implementation Strong collaboration skills working across research and engineering teams Experience with large-scale distributed systems Understanding of AI safety and evaluation best practices

Market Demand

Very high demand with significant growth projected. AI infrastructure roles are crucial as companies scale their AI operations, particularly in evaluation and safety monitoring.

Important Skills

Critical Skills

Deep learning frameworks (PyTorch/TensorFlow) Python development MLOps practices Large-scale system design AI evaluation methodologies

Beneficial Skills

Cloud infrastructure knowledge AI safety principles Distributed systems Research experience Technical writing

Unique Aspects

Direct involvement in Azure OpenAI and cutting-edge AI infrastructure
Opportunity to influence next-generation AI evaluation standards
Access to massive-scale AI deployment experience
Work on systems supporting Microsoft's flagship products

Career Growth

Typical progression to Senior level within 2-3 years, with potential for technical leadership roles in 4-5 years

Potential Next Roles

Senior Machine Learning Engineer Technical Lead - AI Infrastructure AI Architect Principal Engineer

Company Overview

Microsoft

Microsoft's AI Platform organization is central to Azure's competitive position in cloud AI services, particularly with Azure OpenAI and Azure ML offerings

Leader in enterprise AI platforms with significant market share in cloud services
Vancouver office represents a strategic AI development hub with strong connection to headquarters
Innovation-focused environment with emphasis on rapid development and deployment at scale
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