Machine Learning Tools Engineer, SIML

Are you passionate about Generative AI? Are you interested in working on groundbreaking generative modeling technologies to enrich billions of people? We are the Intelligence System Experience (ISE) team within Apple's software organization. The team operates at the intersection of multimodal machine learning and system experiences. Our multidisciplinary ML teams focus on a broad spectrum of areas, including Visual Generative Foundation Models, Multimodal Understanding, Visual Understanding of People, Text, Handwriting, and Scenes, Personalization, Knowledge Extraction, Conversation Analysis, Behavioral Modeling for Proactive Suggestions, and Privacy-Preserving Learning.

These innovations form the foundation of the seamless, intelligent experiences our users enjoy every day. We are looking for a Machine Learning Tools Engineer to help build and evolve the infrastructure, tools, and libraries that power model development and deployment across our organization. The ideal candidate combines strong software engineering fundamentals with ML domain understanding and a deep passion for improving developer experience.

You'll partner closely with researchers, ML engineers, and infra teams to design tools that make training, experimentation, evaluation and inference seamless and efficient. This role is hands-on, user-focused, and requires a balance of building scalable systems and operationally supporting a large and growing user base.

As a Machine Learning Tools Engineer, you will:
* Design, develop, and maintain core ML infrastructure components (training pipelines, experiment tracking, deployment tooling, and monitoring systems).
* Collaborate with ML practitioners to identify pain points and translate them into productized solutions that enhance productivity and reliability.
* Build and maintain Python-based SDKs, CLIs, and APIs that simplify how ML engineers interact with compute, data, and models.
* Ensure tools are robust, performant, and user-friendly, with strong observability and documentation.
* Partner with infrastructure, MLOps, and platform teams to ensure end-to-end system integration and smooth scaling. This is a highly collaborative role that requires curiosity, empathy for users, and a drive to make ML development frictionless.

Prior experience in an ML platform, infrastructure, or productivity tools team. Experience building internal SDKs, CLIs, or automation frameworks for ML or data workflows. Exposure to distributed training, experiment tracking, or model serving infrastructure. Experience supporting large internal or external developer communities.

Bachelor's degree in Computer Science, Engineering, or a related technical field; or equivalent practical experience. 3+ years of experience in software development with strong Python proficiency. Familiarity with machine learning fundamentals and frameworks (e.g., PyTorch, Tensor Flow, JAX).

Experience with Linux systems, containers (Docker), and version control (Git). Strong debugging, analytical, and problem-solving skills. Comfortable operating at the intersection of research and product, coordinating across teams with competing timelines and technical constraints.