Expoint - all jobs in one place

Finding the best job has never been easier

Limitless High-tech career opportunities - Expoint

Apple Senior Machine Learning Engineer Productivity Apps 
United States, California, Cupertino 
580494197

01.06.2024
Key Qualifications
  • 5+ years of experience designing, implementing, evaluating, and deploying machine learning models in production environments.
  • Experience deploying models to memory or compute constrained environments is a plus.
  • Experience with large-scale model training and parallelization is a plus.
  • Experience improving data quality via active learning, core set selection, etc. for images, videos, and text.
  • Experience reading research papers and the ability to build on key ideas.
  • Demonstrated curiosity about the frontier of deep learning including generative AI and multi-modal models.
  • Hands-on experience with GANs, VAEs, Diffusion Models, or Transformers is a plus.
  • Strong programming skills and hands-on experience using one of the popular deep learning toolkits like PyTorch, JAX, or TensorFlow.
  • Strong problem-solving and communication skills.
Education & Experience
MS or PhD in Computer Science, Machine Learning or related field, and 5+ years of significant industry experience delivering products using state-of-the-art machine learning technologies.
Pay & Benefits
  • 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 $170,700 and $300,200, and your base pay will depend on your skills, qualifications, experience, and location.Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
  • Apple is an equal opportunity employer that is committed to inclusion and diversity. We take affirmative action to ensure equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics.