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Machine Learning Engineer, Developer Productivity - Job Opportunity at Apple

Cupertino, USA
Full-time
Senior
Posted: January 19, 2025
On-site
USD 143,100 - 264,200 per year

Benefits

Premium Health Insurance Package with comprehensive medical and dental coverage
Competitive RSU grant program with potential significant upside
Employee Stock Purchase Plan with purchase discount
Comprehensive retirement plan with company matching
Educational reimbursement for career advancement
Discretionary performance bonuses

Key Responsibilities

Design and implement scalable ML solutions for developer productivity enhancement
Build and maintain data processing pipelines and data generation engines
Develop model evaluation infrastructure and inference systems
Drive ML model integration into production software products
Collaborate with applied scientists on NLP applications
Optimize ML infrastructure for cost-effectiveness and maintainability

Requirements

Education

MS in Computer Science or related experience

Experience

Industry experience with applied machine learning and software engineering

Required Skills

Applied machine learning Software engineering Data engineering Natural Language Processing (preferred) Infrastructure development Model deployment
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Sauge AI Market Intelligence

Industry Trends

AI tooling for developer productivity is experiencing rapid growth with major tech companies investing heavily in internal ML-powered development tools Natural Language Processing applications in code analysis and generation are becoming increasingly sophisticated and valuable There's a growing focus on ML-powered automation in software development lifecycle optimization

Salary Evaluation

The offered range is competitive for Silicon Valley, particularly given Apple's strong compensation package. Total compensation including RSUs and bonuses could reach $350,000+ for exceptional candidates

Role Significance

Typically part of a specialized team of 5-8 ML engineers working alongside research scientists and infrastructure engineers
Senior individual contributor role with significant technical ownership and strategic input on ML infrastructure decisions

Key Projects

Developer experience optimization through ML-powered tooling Large-scale code analysis and recommendation systems Automated code review and quality assessment platforms ML pipeline optimization for developer productivity

Success Factors

Deep understanding of ML infrastructure scalability and production deployment challenges Strong software engineering practices and system design principles Ability to bridge research concepts with practical engineering solutions Experience with large-scale data processing and ML pipeline optimization

Market Demand

Very high demand with significant competition for talent, especially in developer tooling ML specialization

Important Skills

Critical Skills

Production ML deployment experience - essential for delivering reliable ML-powered developer tools Strong software engineering fundamentals - crucial for building maintainable and scalable systems NLP expertise - key for understanding and processing code and developer interactions

Beneficial Skills

Cloud infrastructure optimization Developer tool ecosystem knowledge Performance optimization Distributed systems design

Unique Aspects

Opportunity to impact Apple's entire developer ecosystem
Access to unique large-scale developer behavior data
Direct influence on Apple's internal development practices
Exposure to cutting-edge ML applications in developer productivity

Career Growth

2-4 years typical progression timeline with demonstrated impact

Potential Next Roles

Principal Machine Learning Engineer Technical Lead - ML Infrastructure ML Architect Engineering Manager - ML Systems

Company Overview

Apple

Apple's developer tooling team plays a crucial role in maintaining the company's technological edge and developer ecosystem quality

Industry leader with significant resources and influence in shaping developer tools and practices
Silicon Valley headquarters location offers access to cutting-edge ML research and talent
High-performance environment with emphasis on quality, innovation, and significant technical challenges
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