Expoint - all jobs in one place

מציאת משרת הייטק בחברות הטובות ביותר מעולם לא הייתה קלה יותר

Limitless High-tech career opportunities - Expoint

Apple AIML - Staff Machine Learning Engineer Retrieval Ranking Quality SII 
United States, California, Cupertino 
285625791

Today
Minimum Qualifications
  • 7+ year Experience in Machine Learning, NLP, Large Language Models and applying these techniques at scale
  • 3+ year experience in a technical leadership role; overseeing technically complex projects along with mentoring junior engineers, scaling and growing technical teams
  • Strong software engineering skills in mainstream programming languages, such as: Python, Go, C/C++
  • Strong communication skills
  • Bachelors in Computer Science and industry work experience
Preferred Qualifications
  • In-depth knowledge and expertise in Information Retrieval, Ranking or Recommendation Systems
  • Extensive experience in building production quality systems or applications in search, recommendation systems, or information retrieval
  • Experience using ML frameworks (pyTorch, JAX, TensorFlow, XGBoost etc.)
  • Ability to quickly prototype ideas / solutions, and perform critical analysis
  • Background in personalization, user behavior modeling, and data-driven decision-making
  • Advance degree (Master’s or Ph.D.) in Computer Science, Statistics, or related field, or equivalent industry work experience
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 $175,800 and $312,200, 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.