The On-Device Machine Learning team at Apple is responsible for enabling the Research to Production lifecycle of cutting edge machine learning models that power magical user experiences on Apple’s hardware and software platforms. Apple is the best place to do on-device machine learning, and this team sits at the heart of that discipline, interfacing with research, SW engineering, HW engineering, and products. The team builds critical infrastructure that begins with onboarding the latest machine learning architectures to embedded devices, optimization toolkits to optimize these models to better suit the target devices, machine learning compilers and runtimes to execute these models as efficiently as possible, and the benchmarking, analysis and debugging toolchain needed to improve on new model iterations. This infrastructure underpins most of Apple’s critical machine learning workflows across Camera, Siri, Health, Vision, etc., and as such is an integral part of Apple Intelligence. Our group is looking for an ML Infrastructure Engineer, with a focus on ML Performance Visualization. The role entails scaling and extending a significant on-device ML benchmarking service used across Apple.

DESCRIPTION

We are building the first end-to-end developer experience for ML development that, by taking advantage of Apple’s vertical integration, allows developers to iterate on model authoring, optimization, transformation, execution, debugging, profiling and analysis. This role provides a great opportunity to help scale and extend a significant on-device ML benchmarking service used across Apple, in support of a range of devices from small wearables up to the largest Apple Silicon Macs. The role contributes to building the first end-to-end developer experience for ML development that, by taking advantage of Apple’s vertical integration, allows developers to iterate on model authoring, optimization, transformation, execution, debugging, profiling and analysis. The role further offers a learning platform to dig into the latest research about on-device machine learning, an exciting ML frontier! Possible example areas include model visualization, efficient inference algorithms, model compression, and/or ML compilers/run-time. Key responsibilities: * Drive UI/front-end experiences for a ML benchmarking service in a fast-paced environment * Explore intelligent visualization and insights of on-device ML models * Play a key role in maintaining the health and performance of the ML benchmarking service, including debugging failures and addressing user questions / requests. * Collaborate extensively with ML and hardware teams across Apple.

MINIMUM QUALIFICATIONS

• Experience with full-stack web development (e.g. Django) and front-end JavaScript frameworks (e.g. Vue or other comparable frameworks such as React or Angular).
• Strong programming and software design skills in Python.
• Knowledge of ML fundamentals including training regimes, evaluation and deployment/inference.
• A passion/interest for ML, particularly applied to on-device use cases.
• Excellent collaboration and communication skills.

PREFERRED QUALIFICATIONS

• Masters or PhDs in Computer Science or relevant disciplines.
• Experience with any ML authoring framework (PyTorch, TensorFlow, JAX, etc.) is a strong plus, particularly on-device ML frameworks such as CoreML, TFLite or ExecuTorch.
• Back-end system skills including containers (docker), cloud orchestration (Kubernetes), database (SQL, Postgres)
• Experience with standard ML architectures such as Transformers, CNNs or Stable Diffusion a strong plus.

Please refer the Job description for details