Machine Learning Engineer — Trust and Safety (Account Trust)
Description For Machine Learning Engineer — Trust and Safety (Account Trust)
The Trust and Safety group at Apple is seeking a talented Machine Learning Engineer to join their team focused on ensuring genuine and safe experiences for Apple's service users. This role is critical in protecting various systems, including Apple's account creation flows and iMessage spam prevention.
As a Machine Learning Engineer in the Trust and Safety team, you'll be responsible for analyzing vast amounts of data to generate actionable insights that enhance customer safety. You'll work at the intersection of data science, software engineering, and machine learning research, developing sophisticated solutions to combat fraud and maintain the integrity of Apple's ecosystem.
The ideal candidate will have a strong background in machine learning, demonstrated experience in anti-fraud systems, and exceptional analytical abilities. You'll collaborate with cross-functional teams to develop and implement strategic, long-term fraud prevention solutions while continuously expanding your technical expertise.
Key aspects of the role include maintaining deep knowledge of Apple's services and protection systems, analyzing complex user behavior patterns, and building partnerships to strengthen security measures. You'll need to effectively communicate technical concepts to various audiences and stay ahead of potential security threats.
The position offers competitive compensation ($175,800 - $312,200) plus comprehensive benefits including medical coverage, stock options, and educational support. Join Apple's mission to create safe and trustworthy experiences for millions of users worldwide while working with cutting-edge technology and talented professionals in Cupertino.
Responsibilities For Machine Learning Engineer — Trust and Safety (Account Trust)
- Maintain a deep understanding of Apple's account types, services, and evolving protection systems
- Simplify complex systems and communicate technical concepts to non-technical audiences
- Analyze user behavior from diverse data sources, building narratives that explain fraudulent activity and attack methods
- Build strong partnerships to close data gaps and mitigate attack vectors
- Identify weaknesses, propose better fraud-fighting tools, and anticipate attacker adaptations
Requirements For Machine Learning Engineer — Trust and Safety (Account Trust)
- Proven experience in anti-fraud with at least two complex investigations in incomplete data environments
- 3+ years of experience with big data tools (SQL, Spark, Splunk, Python, Jupyter Notebook)
- Familiarity with machine learning algorithms including classifiers, clustering algorithms, and anomaly detection
- Experience collaborating across engineering and non-engineering teams
Benefits For Machine Learning Engineer — Trust and Safety (Account Trust)
- Comprehensive medical and dental coverage
- Retirement benefits
- Discounted products and free services
- Education reimbursement
- Stock options and employee stock purchase plan
- Discretionary bonuses
- Relocation assistance
