Machine Learning Engineer, Apple Intelligence

Apple Apple · Big Tech · Bengaluru, Karnataka, India · Software and Services

ML Engineer focused on building and optimizing generative models for international languages, covering the full pipeline from data preprocessing to deployment.

What you'd actually do

  1. Focus exclusively on building and optimizing generative models for international languages.
  2. Own the entire generative modeling pipeline, from data preprocessing and model architecture design to training, evaluation, and deployment.
  3. Prioritize working with a variety of popular international languages, ensuring our models are culturally and linguistically adaptable.

Skills

Required

  • Python
  • Objective C
  • Swift
  • PyTorch
  • TensorFlow
  • NLP algorithms
  • tokenization
  • language modelling
  • text decoding
  • text classifier

Nice to have

  • implementing basic optimizers
  • implementing regularizations
  • formulating and implementing loss functions
  • parameter tuning
  • model training
  • model evaluation
  • reproducing state-of-the-art research experiments
  • revising state-of-the-art research experiments
  • addressing accuracy bottlenecks
  • addressing performance bottlenecks
  • distributed training
  • distributed inference
  • benchmarking model compressing methods
  • high-quality codes
  • complex and large repositories
  • implementing new optimizer
  • implementing loss functions
  • algorithm optimizations
  • refactoring code-base
  • redesigning code-base
  • processing large data set efficiently
  • processing large data set accurately
  • automated synthesis pipeline
  • automated training pipeline
  • automated evaluation pipeline
  • object-oriented design patterns
  • multi-modal modeling
  • presenting plans
  • presenting progress
  • presenting results
  • presenting demos
  • NLP modeling for Indian languages
  • Strong problem solving
  • drive what matters
  • Results oriented
  • work in a fast-paced environment
  • fight for excellence
  • Ability to communicate effectively
  • innovate to the details

What the JD emphasized

  • hard-working
  • dedicated
  • outstanding
  • most advanced
  • hard-working
  • dedicated
  • outstanding
  • most advanced
  • end-to-end solutions
  • building and optimizing
  • entire generative modeling pipeline
  • data preprocessing
  • model architecture design
  • training
  • evaluation
  • deployment
  • variety of popular international languages
  • culturally and linguistically adaptable
  • deep interest in natural language processing
  • talent for building generative models
  • work seamlessly across languages
  • meaningful impact
  • 4+yrs of machine learning expertise
  • Strong programming using Python/Objective C/Swift
  • Good exposure to Deep Learning libraries like PyTorch and TensorFlow
  • Thorough experience with common NLP algorithms and applications, including tokenization, language modelling, text decoding, text classifier etc.
  • Actively exercising machine learning techniques, including implementing basic optimizers and regularizations; formulating and implementing loss functions for given tasks, applying insightful parameter tuning in model training and evaluation, reproducing and revising state-of-the-art research experiments; addressing accuracy and performance bottlenecks in distributed training and inference, and benchmarking different model compressing methods
  • Actively programming with high-quality codes across complex and large repositories, including implementing new optimizer or loss functions, algorithm optimizations for critical performance or accuracy, refactoring or redesigning of existing code-base for improved robustness and flexibility, processing large data set efficiently and accurately, establishing automated synthesis/training/evaluation pipeline across multiple sets of internal and external APIs, and applying common object-oriented design patterns
  • Experience of multi-modal modeling, presenting plans, progress, and results or demos regularly and concisely
  • Experience in NLP modeling for Indian languages is desired.
  • Strong problem solving and drive what matters
  • Results oriented with a desire to work in a fast-paced and fight for excellence.
  • Ability to communicate effectively and innovate to the details.

Other signals

  • generative modeling pipelines
  • international languages
  • end-to-end solutions
  • data preprocessing
  • model architecture design
  • training
  • evaluation
  • deployment