Apple is looking to solve the problem of providing a unified, rich, and up-to-date set of Points of Interest (POIs) to hundreds of millions of Apple Maps users across the world by aggregating, processing, filtering, and conflating data from many sources and multiple modalities.
Requirements
- 5+ years of experience in building large scale machine learning systems
- 2+ years of experience in one or more of the following ML areas: generative AI models (e.g. Transformers, LLMs, VLMs, etc), NLP and text data, Computer Vision
- Intuitive understanding of machine learning algorithms, supervised and unsupervised modeling techniques and their performance characteristics
- Experience working with large scale and real world datasets
- Deep learning, computer vision, topic modeling, graph algorithms are pluses
- Strong programming skills and hands-on experience with machine learning tools and libraries such as PyTorch, TensorFlow, Scikit-learn
- Knowledge of Spark, Apache Hadoop, Solr/Lucene, Cassandra, and related big data technologies
Responsibilities
- Converting abstract, high-level goals into concrete, measurable requirements
- Proposing, implementing, evaluating, and shipping different AI/ML technologies and resulting data to achieve a given task
- Collaborating with various partners, including engineering orgs and designers to architect the best overall system
- Taking projects from initial data mining and research through all stages of prototyping, development, and final integration of AI / ML data solutions into the production code
- Building large scale machine learning systems
- Working with large scale and real world datasets
- Delivering models that render high quality results
Other
- Masters or PhD degree in Machine Learning, Computer Science, Electrical/Computer Engineering, or related fields
- Excellent independent problem-solving skills
- Excellent written and oral communication skills
- Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services
- Relocation might be eligible for discretionary bonuses or commission payments
