Machine Learning Engineer

Apple Inc.
Santa Clara, CA, United States
2 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
3 years minimum
Compensation
$175,000.0
Working hours
Regular working hours

Tech stack

Java (Programming Language) Artificial Intelligence Apple Products Computer Vision C++ (Programming Language) Computer Programming Email Filtering Information Retrieval Python (Programming Language) Machine Learning Natural Language Processing Tensorflow
+7 more
Search Technologies Pytorch Deep Learning Siri Information Technology Machine Learning Operations Golang

Job description

is redefining how hundreds of millions of people use their devices to get information. We are an Applied ML team pushing the limits on realtime augmented information retrieval and generation, information safety and search technologies, while also responsible for a few user facing production services. We are part of a wider effort to power information across a variety of Apple products - including Siri, Spotlight, Safari, Messages, Lookup, and more. We are deeply committed to ensuring that our platform remains a safe, welcoming, and trustworthy environment for everyone., We are looking for a highly skilled Machine Learning Engineer to join our Search Safety team. In this role, you will build and deploy state-of-the-art machine learning models designed to detect, demote, and filter harmful, abusive, or policy-violating content across our search ecosystem. You will work at the intersection of Search, Natural Language Processing (NLP), Image and Trust & Safety, addressing complex challenges like query intent understanding, adversarial evasion, jailbreaking, and multimodal content filtering. If you are passionate about protecting users and building robust ML systems at scale, we want you on our team.

Requirements

Experience working on content moderation, spam detection, fraud, or Trust & Safety ML teams.

Experience in red-teaming, adversarial training, or robustness evaluation of ML models.

Building machine-learned models and integrating safety signals directly into the search ranking and retrieval pipelines, balancing safety constraints with search relevance and user engagement.

MS or PhD in Computer Science, Artificial Intelligence, Machine Learning, Safety, Computer Vision or related fieldor equivalent work experience

Minimum Qualifications

3+ years of industry related experience, working in collaborative environments

Experience with utilizing PyTorch, TensorFlow, or JAX for training and deploying deep learning models

Understanding product requirements then translating them into modeling tasks and engineering tasks

Proficient in at least two programing languages such as: Python, Go, Java, C/C++

BS in Computer Science, Artificial Intelligence, Machine Learning, Safety, Computer Vision or related field or equivalent work experience

Benefits & conditions

At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $175,000 and $263,300, and your base pay will depend on your skills, qualifications, experience, and location.

Apple employees also have the opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple’s Employee Stock Purchase Plan. You’ll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits

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Apply on www.themuse.com
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