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Senior Applied Scientist - Job Opportunity at Microsoft

Reading, GB
Full-time
Senior
Posted: May 18, 2025
On-site
GBP 90,000 - 130,000 per year based on Reading market rates for senior AI roles

Benefits

Cutting-edge AI technology exposure
Access to next-generation hardware
Collaborative research environment
Professional development opportunities
Startup-like culture within established company

Key Responsibilities

Lead development and implementation of AI model optimization techniques with focus on on-device performance
Architect and develop Python/C++ libraries for NPU-optimized LLM implementations
Drive cross-functional innovation initiatives with external partners
Establish technical validation frameworks and prototyping methodologies

Requirements

Education

Bachelor's, Master's, or PhD in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field

Experience

Significant ML engineering or ML research experience required

Required Skills

C++ Python git Machine Learning Model optimization NPU experience AML/ADO pipelines Embedded systems Windows development Self-motivation Collaboration Communication Attention to detail
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Sauge AI Market Intelligence

Industry Trends

The focus on on-device AI optimization reflects a broader industry shift towards edge computing and reduced cloud dependency NPU-specific optimization expertise is becoming increasingly valuable as mobile devices integrate dedicated AI hardware The convergence of ML engineering and systems programming indicates a growing need for full-stack AI expertise

Role Significance

Likely part of a specialized team of 5-8 engineers and scientists, with matrix reporting to broader research and product organizations
Senior individual contributor role with significant technical decision-making authority and potential technical leadership responsibilities

Key Projects

On-device LLM optimization and deployment Multi-modal AI system development Hardware-software co-optimization research ML pipeline development and automation

Success Factors

Deep understanding of ML optimization techniques and hardware architecture Ability to bridge theoretical ML concepts with practical implementation constraints Strong collaboration skills across research and product teams Track record of delivering production-quality ML systems

Market Demand

Very High - Edge AI optimization specialists are currently among the most sought-after professionals in tech, with demand expected to grow as more devices incorporate AI capabilities

Important Skills

Critical Skills

Deep ML optimization expertise - essential for achieving performance targets on resource-constrained devices Systems programming proficiency - crucial for low-level optimization and hardware interface Cross-functional collaboration skills - vital for working across research and product teams

Beneficial Skills

Knowledge of specific hardware architectures Experience with ML deployment pipelines Familiarity with Windows development ecosystem

Unique Aspects

Rare opportunity to work on hardware-optimized AI systems at scale
Direct impact on next-generation Microsoft products
Combination of research freedom with product impact
Access to advanced hardware prototypes

Career Growth

2-4 years in role typical before advancement, depending on impact and organizational growth

Potential Next Roles

Principal Applied Scientist Technical Lead - AI Systems Research Manager AI Architecture Lead

Company Overview

Microsoft

Microsoft's Applied Sciences Group operates as an innovation hub, bridging research and product development in emerging technologies

Industry leader in enterprise AI and cloud computing, with growing presence in consumer AI applications
Reading location serves as a key technical hub for Microsoft's UK operations, with strong connections to European research centers
Innovation-focused environment combining startup agility with enterprise resources and stability
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