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Applied Scientist II - Microsoft 365 Copilot - Job Opportunity at Microsoft

Vancouver, Canada
Full-time
Mid-level
Posted: June 2, 2025
Remote
CAD 83,600 - CAD 159,600 per year

Benefits

Complete remote work flexibility enabling global talent access and work-life balance optimization
Industry-leading healthcare coverage providing comprehensive medical, dental, and mental health support
Extensive educational resources including learning platforms, conference attendance, and skill development programs
Employee discounts on Microsoft products and services enhancing personal technology capabilities
Robust savings and investment programs including 401k matching and stock purchase options
Progressive maternity and paternity leave policies supporting family life transitions
Generous paid time off policies promoting employee well-being and preventing burnout
Corporate giving programs enabling employee philanthropy and community impact
Comprehensive networking opportunities facilitating professional relationship building and career advancement

Key Responsibilities

Drive strategic evolution of Microsoft's core orchestrator systems to enhance reasoning capabilities, reduce response latency, and pioneer multi-modal agent-based architectures that directly impact hundreds of millions of global users
Lead advanced model training initiatives including post-training optimization through fine-tuning and reinforcement learning methodologies while establishing high-quality data curation standards that define industry benchmarks
Execute end-to-end model-driven feature development from conceptualization through production deployment, incorporating sophisticated evaluation frameworks, performance metrics, and A/B testing methodologies that inform product strategy
Establish expertise in specialized research domains while developing comprehensive understanding of service platforms and staying current with cutting-edge industry technologies and methodologies
Implement advanced research strategies guided by senior leadership while incorporating state-of-the-art methodologies and developing deep specialization in emerging applied sciences areas
Foster positive team culture through mentorship of entry-level scientists, support onboarding processes, and maintain strategic external professional networks for talent identification and knowledge exchange
Document and disseminate research findings to drive innovation across organizational groups while ensuring compliance with ethics and privacy policies in all research and data collection activities

Requirements

Education

Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field OR equivalent experience

Experience

2+ years related experience (e.g., statistics, predictive analytics, research) with Bachelor's OR 1+ year(s) related experience with Master's OR equivalent with Doctorate, plus 1+ years of experience applying Machine Learning techniques

Required Skills

2+ years of experience coding in Python, C++, C#, C or Java 1+ years of experience applying Machine Learning techniques Statistics and predictive analytics Research methodologies Deep learning and NLP Multimodality models Model optimization

Certifications

Microsoft Cloud Background Check clearance required
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Sauge AI Market Intelligence

Industry Trends

The enterprise AI market is experiencing unprecedented growth with organizations rapidly adopting large language models for productivity enhancement, creating massive demand for applied scientists who can bridge research and production deployment. Microsoft's Copilot platform represents a significant market shift toward integrated AI-first productivity tools that are reshaping how enterprises approach workflow automation and decision support systems. Multi-modal AI systems combining text, voice, and visual processing are becoming the new standard for enterprise applications, requiring scientists with expertise in orchestrating complex model interactions and developing agent-based architectures that can handle diverse input types and user contexts. The field is witnessing a critical transition from pure research to applied AI engineering, where professionals must demonstrate capabilities in both cutting-edge model development and production-scale deployment, including post-training optimization techniques like reinforcement learning and fine-tuning methodologies.

Salary Evaluation

The provided CAD 83,600 - CAD 159,600 range (approximately USD 62,000 - USD 118,000) is competitive for the Canadian market and reflects Microsoft's strategic investment in AI talent. This compensation aligns with mid-level applied scientist positions in major tech companies, with the range accounting for experience variation within the IC3 level and Vancouver's growing tech ecosystem.

Role Significance

Applied scientists typically work within cross-functional teams of 8-15 members including researchers, engineers, product managers, and data scientists, with this role likely involving collaboration across multiple teams given the scope of Microsoft 365 Copilot's platform integration.
This IC3-level position represents a mid-level applied scientist role with significant technical leadership responsibilities, including mentoring junior team members and driving core system evolution for one of Microsoft's most strategic AI products. The role combines hands-on technical execution with strategic thinking about next-generation AI capabilities.

Key Projects

Development and optimization of large language model orchestration systems handling millions of daily user interactions Implementation of multi-modal AI agents capable of processing text, code, and document-based queries across Microsoft 365 applications Design and execution of advanced model training pipelines incorporating reinforcement learning and fine-tuning techniques for enterprise-specific use cases

Success Factors

Deep technical expertise in both theoretical machine learning concepts and practical implementation challenges, particularly in large-scale distributed systems that must maintain high availability and performance standards. Success requires the ability to translate cutting-edge research into production-ready solutions that can handle enterprise-level usage patterns. Strong collaboration and communication skills for working effectively across research and engineering teams, with the ability to mentor junior scientists while learning from senior researchers. The role demands someone who can bridge the gap between academic research and commercial product development. Adaptability and continuous learning mindset given the rapidly evolving nature of AI technology, particularly in areas like multi-modal processing and agent-based systems where best practices are still being established across the industry.

Market Demand

Extremely high demand driven by the AI revolution in enterprise software, with Microsoft's massive investment in Copilot technology creating numerous opportunities for applied scientists who can work at the intersection of research and production systems.

Important Skills

Critical Skills

Python programming expertise is absolutely essential as it serves as the primary language for machine learning research and development, with Microsoft's AI infrastructure heavily built on Python-based frameworks and libraries. Proficiency in Python enables rapid prototyping, model development, and integration with existing production systems. Machine learning and deep learning knowledge forms the core foundation for this role, as applied scientists must understand both theoretical concepts and practical implementation challenges when working with large language models, reinforcement learning, and multi-modal AI systems at enterprise scale. Experience with large-scale distributed systems and production AI deployment is crucial, as Microsoft 365 Copilot requires systems that can handle millions of concurrent users while maintaining low latency and high reliability standards.

Beneficial Skills

Research publication experience demonstrates ability to contribute to the broader AI community and stay current with cutting-edge developments, which is valuable for a role that bridges research and product development Knowledge of cloud computing platforms, particularly Microsoft Azure, provides additional value for optimizing AI workloads and understanding the infrastructure constraints and opportunities in enterprise AI deployment Understanding of software engineering best practices including version control, testing, and continuous integration becomes increasingly important as AI systems mature and require robust development processes

Unique Aspects

Direct impact on hundreds of millions of users through Microsoft 365 Copilot, providing rare opportunity to see research contributions deployed at unprecedented scale across global enterprise environments
Access to cutting-edge AI infrastructure and partnerships with leading research organizations like OpenAI, enabling work with state-of-the-art models and computational resources
Integration with Microsoft's comprehensive ecosystem spanning cloud computing, productivity software, and developer tools, allowing for holistic AI solution development
Opportunity to work on multi-modal AI systems that represent the next generation of human-computer interaction paradigms

Career Growth

Progression to Senior Applied Scientist typically occurs within 2-3 years with demonstrated impact on product metrics and technical leadership contributions, while advancement to Principal level or management roles generally requires 4-6 years of consistent high performance and strategic thinking.

Potential Next Roles

Senior Applied Scientist (IC4) leading larger research initiatives and driving technical strategy for major product features Principal Applied Scientist (IC5) setting research direction for entire product areas and representing Microsoft in external technical communities Applied Science Manager transitioning to people leadership while maintaining technical involvement in strategic research projects Research Scientist roles in Microsoft Research focusing on longer-term fundamental research in AI and machine learning

Company Overview

Microsoft

Microsoft stands as one of the world's largest technology companies with a market capitalization exceeding $2 trillion, leading the enterprise software market through its comprehensive suite of productivity tools, cloud services, and developer platforms. The company has successfully positioned itself at the forefront of the AI revolution through strategic partnerships with OpenAI and massive investments in generative AI technology integration across its product portfolio.

Microsoft maintains a dominant position in enterprise software with Microsoft 365 serving over 400 million subscribers worldwide, while its strategic AI initiatives have strengthened its competitive advantage against Google, Amazon, and other technology giants in the rapidly evolving AI-driven productivity space.
Vancouver serves as a critical hub for Microsoft's AI and research operations, benefiting from Canada's strong AI research ecosystem, favorable immigration policies for international talent, and proximity to major universities producing top-tier computer science and AI specialists.
Microsoft has undergone significant cultural transformation under current leadership, emphasizing growth mindset, collaboration, and innovation while maintaining its commitment to diversity and inclusion. The company's remote-first policies and focus on employee well-being have made it an attractive destination for top AI talent globally.
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