Senior Machine Learning Engineer
@ Apple

Cupertino, California, United States
$180,000
On Site
Full Time
Posted 29 days ago

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About Apple

Apple is where individual imaginations gather together, committing to values that inspire innovation. Every product, service, and experience is crafted from the best ideas of diverse teams, making the impossible possible.

Role Overview: Senior Machine Learning Engineer

Join the ML Systems Evaluation Engineering (MLSEE) team at Apple Intelligence, where you will contribute to revolutionary advancements in Siri and other AIML products by evaluating and enhancing AI/ML capabilities for conversational assistants.

Key Responsibilities

  • Deliver offline evaluation insights for model improvements.
  • Develop and manage large datasets for evaluation.
  • Leverage large language models to assess user experience.
  • Create adversarial scenarios using generative AI.
  • Collaborate with cross-functional teams to enhance product outcomes.

Minimum Qualifications

  • 7+ years applying machine learning to real-world problems.
  • Experience with natural language products/technologies.
  • Expertise in managing ML datasets.
  • MS/PhD in Machine Learning, Computer Science or similar.
  • Excellent Python programming skills.

Preferred Qualifications

  • Strong Conversational AI domain knowledge.
  • Problem solving, critical thinking, and communication skills.
  • Expert in evaluating large language models and agents.
  • Continual learner with a passion for new technologies.
  • Solid background in systems engineering and ML product lifecycle.

Key skills/competency

Machine Learning, Conversational AI, Python, Evaluation, Generative AI, Datasets, LLMs, Systems Engineering, Natural Language Processing, Product Lifecycle

How to Get Hired at Apple

🎯 Tips for Getting Hired

  • Research Apple's culture: Explore their innovation and diversity values.
  • Tailor your resume: Highlight ML and AI project successes.
  • Showcase technical skills: Emphasize Python and dataset management.
  • Prepare for interviews: Practice evaluation techniques and problem solving.

📝 Interview Preparation Advice

Technical Preparation

Brush up on Python coding skills.
Review ML model evaluation techniques.
Practice dataset management exercises.
Study large language model applications.

Behavioral Questions

Discuss a challenging project effectively.
Explain teamwork in ML projects.
Describe handling tight deadlines.
Demonstrate problem-solving under pressure.

Frequently Asked Questions