About the role

Aplyr's Quick Take

This role is for a Machine Learning Engineer focused on enhancing safety in Apple's communication platforms by developing anti-fraud solutions. You'll be building ML tools and collaborating with various teams to tackle complex data challenges and improve user experience. It's primarily an individual contributor role with a strong emphasis on technical skills and cross-team collaboration.

Good fit

Ideal candidates have 3+ years of experience in machine learning and anti-fraud systems, with strong Python skills. A collaborative mindset and the ability to work with both technical and non-technical stakeholders are essential.

Worth noting

The position emphasizes self-directed research and the ability to handle incomplete data, which may be challenging for some. The role also involves significant collaboration across multiple teams, which could be a plus for those who enjoy teamwork.

Summary

The Trust and Safety group at Apple is responsible for ensuring that users of Apple’s services and products have genuine and safe experiences. Within Trust and Safety, our team works to protect Apple’s communication apps and related platforms from spam and other abuse. The solutions we deploy help us keep Apple ecosystem safe, while mitigating constant attack by external actors. We are seeking a machine learning engineer who will strive to turn data into actionable insights that improve safe customer experience. Successful candidates will have a demonstrated history of self-directed research and investigations spanning sophisticated, interdependent systems that led to novel insights directly impacting well-defined success metrics.

Description

Success in this role is defined by your ability to: •Simplify complex systems and work with technical and non-technical stakeholders to build solutions to align for specific use cases. •Build machine learning tooling to facilitate various phases of the ML lifecycle from model training, data ETL, end-to-end model evaluation and deployment. •Deliver reusable and easy-to-use tooling to integrate with existing data and machine learning systems. •Build strong partnerships to close data gaps and mitigate attack vectors. •Identify weaknesses, propose better fraud-fighting tools, and anticipate attacker adaptations. This role requires exceptional collaboration across Data Science, Software Engineering, and Machine Learning Research. You’ll work with partner teams to develop strategic, long-term fraud prevention solutions while continuously enhancing your software engineering and machine learning expertise.

Minimum Qualifications

Proven experience in anti-fraud (or similar) with at least two complex investigations in incomplete data environments, demonstrating initiative and measurable impact. Strong understanding of machine learning algorithms (including classifiers, clustering algorithms, and anomaly detection), especially in the context of LLMs. 3+ years of proficiency in Python, including machine learning packages like Jax/Tensorflow or PyTorch. 3+ years of experience with big data tools (SQL, Spark, Splunk, Python, Jupyter Notebook). Experience collaborating across engineering and non-engineering teams. Strong interpersonal verbal and written communication skills with the ability to work effectively across internal and external organizations and virtual teams. BS/BA or equivalent degree in computer science or similar (preferred).

Preferred Qualifications

5+ years experience with Python, Scala, Java, or similar, including relevant libraries (e.g., scikit-learn, TensorFlow, PyTorch, Spark MLlib). 5+ years of industry software development experience using source control (e.g., Git). Advanced degree (MS/PhD) in a quantitative field (Computer Science, Statistics, Mathematics, Operations Research). Hands-on experience implementing machine learning solutions (classifiers, clustering, anomaly detection). Experience building scalable deep learning systems. Experience with large scale data infrastructure. Curiosity, integrity, and a passion for learning and enhancing the Apple customer experience. Excellent interpersonal, written, and verbal communication skills Curiosity, passion for learning, high personal integrity, and a dedication to improving the Apple customer experience

Skills & Tags

rust machine learning

Aplyr's read

Apple is a tech giant known for its sleek design and innovation, attracting top talent in engineering, design, and business operations.
Synthesized from recent postings & public sources

What's promising

•Apple consistently leads in tech innovation with a strong focus on design and user experience.
•The company's global brand recognition offers employees a prestigious platform for career growth.
•Apple's robust ecosystem integrates hardware, software, and services, creating diverse job opportunities.

What to watch

•High-pressure work environment with demanding deadlines can impact work-life balance.
•Apple's secretive culture may limit transparency and cross-departmental communication.
•Dependence on hardware sales makes the company vulnerable to market saturation risks.

Why Apple

•Apple's design philosophy emphasizes simplicity and elegance, setting it apart in the tech industry.
•The company has a unique retail presence with its own stores enhancing customer experience.
•Apple's closed ecosystem creates a seamless integration across its products, unmatched by competitors.

Aplyr’s read is generated by AI from public sources. Was it useful?

About Apple

Apple

apple.com

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AAPL$295.63+1.39%

Apple Inc. is a leading technology company known for its innovative consumer electronics, software, and services. The company designs and manufactures products such as the iPhone, iPad, Mac computers, and wearables, significantly influencing the tech industry and consumer behavior worldwide.