At Apple, the business problem is to create products that enrich people's lives, specifically in the Ad Platforms group, which aims to enable effective advertising while protecting user privacy.
Requirements
- Proven track record of designing and scaling robust ML infrastructure and frameworks that support both training and inference across teams and orgs
- Experience of model quantization, tensor parallelism, and inference optimizations (e.g ONNX Runtime, TensorRT, vLLM)
- Experience building machine learning models using frameworks like PyTorch, TensorFlow
- Prior experience in advertising industry, federated learning and privacy-preserving ML techniques
- Led development of foundational AI/ML platforms and tooling including Feature Stores, Vector DB to accelerate team productivity and model lifecycle management
- Experience working on distributed systems (e.g Ray, Spark, Kubernetes)
- Experience performance tuning & trouble-shooting
Responsibilities
- Design and develop secure and scalable back-end systems
- Build high-performing, elegant systems from the ground up, in close partnerships with various teams
- Define and refine architectures to meet the unique ad network challenges
- Build machine learning products which deliver on Apple's privacy commitments and change the way advertising works with data
- Design, develop, and build world-class platform capabilities that will enable Ad Platforms teams to improve and scale our ML features, models, and applications
- Work closely with engineers and data scientists to design, develop, and build world-class platform capabilities
- Possess keen judgment in selecting technologies and building the right solution for the interesting challenges
Other
- Results oriented with a desire to work in a fast-paced and collaborative work environment
- Ability to communicate effectively, both written and verbal, with technical and non-technical multi-functional teams
- PhD/MS/BS in computer science or related field with 8+ years of experience in machine learning and strong software engineering skills
- Recognized as a technical leader and mentor, supports the growth of engineers through code/design reviews, working groups, and internal knowledge sharing
- Pride in building tools to automate routine tasks, organized & detailed
