Software Engineer (AI/ML), Enterprise Systems

Austin, Texas, United States

Apple

We’re a diverse collective of thinkers and doers, continually reimagining what’s possible to help us all do what we love in new ways.

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Summary

Posted: Apr 25, 2024

Role Number:200548837

Do you love understanding every detail of how new technologies work? Join the team that serves as Apple’s nerve center, our Information Systems and Technology group. There are countless ways you’ll contribute here, whether you’re coordinating technology needs for product launches, designing music solutions for retail locations, or ensuring the strength of in-store Wi-Fi connections. From Apple Pay to the Apple website to our data centers around the globe, you’ll help design and manage the massive systems that countless employees and customers rely on every day. You’ll also build custom tools for employees, empowering them to solve complex problems on their own. Join our team, and together we’ll explore all the ways to improve how Apple operates, freeing our employees to do what they do best: craft magical experiences for our customers. The Global Business Intelligence team provides data services, analytics, reporting, and data science solutions to Apple’s business groups, including Retail, iTunes, Marketing, AppleCare, Operations, Finance, and Sales. These solutions are built on top of an end-to-end machine learning platform with sophisticated AI capabilities. This position is an extraordinary opportunity for a competent, experienced, and results-oriented Software Engineer (AI/ML) to define and build some of the best-in-class machine learning solutions and tools for Apple.

Key Qualifications


  • 3+ years of machine learning engineering experience in feature engineering, model training, model serving, model monitoring and model refresh management.
  • Experience developing AI/ML systems at scale in production or in high-impact research environments.
  • Passionate about computer vision, natural language processing, especially in LLMs and Generative AI systems.
  • Knowledge with the common frameworks and tools such as PyTorch or TensorFlow.
  • Proven experience with transformer models such as BERT, GPT etc., and a proven understanding of their underlying principles is a plus
  • Strong coding and software engineering skills, and familiarity with software engineering principles around testing, code reviews and deployment.


Description


As a Software Engineer (AI/ML), you will work on building intelligent systems to democratize AI across a wide range of solutions within Apple. You will drive the development and deployment of state-of-the-art AI models and systems that directly impact the capabilities and performance of Apple’s products and services. You will implement robust, scalable ML infrastructure, including data storage, processing, and model serving components, to support seamless integration of AI/ML models into production environments. You will develop novel feature engineering, data augmentation, prompt engineering and fine-tuning frameworks that achieve optimal performance on specific tasks and domains. You will design and implement automated ML pipelines for data preprocessing, feature engineering, model training, hyper-parameter tuning, and model evaluation, enabling rapid experimentation and iteration. You will also implement advanced model compression and optimization techniques to reduce the resource footprint of language models while preserving their performance. There are massive opportunities for you deliver impactful influences to Apple.

Education & Experience


BS in Computer Science or related field or equivalent.


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* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

Tags: BERT Business Intelligence Computer Science Computer Vision Engineering Feature engineering Finance Generative AI GPT LLMs Machine Learning ML infrastructure ML models Model training NLP Pipelines Prompt engineering PyTorch Research TensorFlow Testing

Perks/benefits: Career development

Region: North America
Country: United States
Job stats:  3  1  0

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