Machine Learning Engineer

Apple is where individual imaginations gather together, committing to the values that lead to great work. Every new product we build, service we create, or experience we deliver is the result of us making each other’s ideas stronger. The diversity of our people and their thinking inspires the innovation that runs through everything we do. When we bring everybody in, we can do the best work of our lives. Here, you’ll do more than join something — you’ll add something.

The Special Projects team at Apple is developing novel user-facing conversational features that leverage the multimodal capabilities of state-of-the-art foundation models. We are looking for a highly skilled Machine Learning Engineer to build the processes to evaluate these experiences. A successful candidate is experienced in evaluating complex foundation model driven systems end-to-end, translating subjective product requirements into objective criteria, and has strong statistical analysis skills.

• Design and implement processes for evaluating multi-modal generative models for end-to-end product requirements.
• Work closely with ML Researchers to define evaluation criteria and methodology to systematically evaluate foundation models.
• Experimental design for testing models/systems under test
• Conduct robust statistical analysis to identify model deficiencies and failure states.

• Master’s degree in Computer Science or other STEM majors
• 2+ years of hands-on industry experience with product focused statistical analysis for generative models
• Proficiency in Python and ML frameworks (Pytorch or Tensorflow)

• PhD in Computer Science, Machine Learning, Statistics or a related technical field
• 5+ years of hands-on industry experience with product focused statistical analysis for generative models
• Experience with experimental design, A/B testing and Failure Analysis
• Proficiency in training and evaluation of foundation models and frameworks
• A track record of publications or technical presentations in Machine Learning journals or conferences
• Excellent at communication and cross functional collaboration