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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # ML Platform Engineer - **Company:** Apple Inc. - **Location:** Sunnyvale, CA, United States - **Experience:** Experienced - **Salary:** $147,400.0 - $272,100.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Computer Vision, Microsoft Azure, Big Data, C++ (Programming Language), Cloud Computing, Nvidia CUDA, Computer Programming, Core Foundation, Data Cleansing, Information Engineering, Data Transformation, DevOps, Distributed Computing Environment, Distributed Systems, Python (Programming Language), Machine Learning, OpenCL, Tensorflow, Azure Machine Learning, Software Engineering, Google Cloud, Data Ingestion, Pytorch, Large Language Models, Apache Spark, Gpu Programming, Containerization, Kubernetes, Information Technology, Hardware Acceleration, Machine Learning Operations, Data Pipelines, Docker - **Published:** May 21, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=6f38a126d31734fc ## About the Role Do you have experience in Software engineering?, Do you have a Master's degree?, We're starting to see the incredible potential of multimodal foundation and large language models, and many applications in the computer vision and machine learning domain that previously appeared infeasible are now within reach. We are looking for highly motivated and skilled Machine Learning Platform Engineers to join our team in the VCV group and help us enable that potential for realtime human understanding on Apple devices., Master's degree in Computer Science, Machine Learning, or related technical field 2+ years of experience in ML infrastructure, platform engineering, or production ML systems Experience with Apple's frameworks including CoreFoundation, RealityKit, and CoreML Hands-on experience with CI/CD pipelines, DevOps practices, and infrastructure as code Experience with containerization technologies (Docker, Kubernetes) and orchestration systems Knowledge of cloud platforms (AWS, GCP, Azure) and distributed computing frameworks (Spark, Ray, etc.) Experience with GPU programming and hardware acceleration (Metal, CUDA, OpenCL) Minimum Qualifications Bachelor's degree in Computer Science, Software Engineering, or related technical field, or equivalent practical experience 2+ years of relevant industry experience in software engineering, machine learning infrastructure, or related fields Strong programming skills in Python, C++, and/or Swift Experience with machine learning frameworks such as PyTorch, TensorFlow, or JAX Knowledge of machine learning model development lifecycle, including data preprocessing, model training, evaluation, and deployment Experience with distributed systems, cloud computing, or large-scale data processing Strong foundational knowledge in Computer Science and software engineering principles ## Description The VCV org has pioneered human-centric real-time features such as FaceID, FaceKit, and Gaze and Hand gesture control which have changed the way millions of users interact with their devices. We balance research and product requirements to deliver Apple quality, pioneering experiences, innovating through the full stack, and partnering with HW, SW and AI teams to shape Apple's products and bring our vision to life., As part of the VCV team, you will build and maintain the critical infrastructure that enables machine learning at scale across Apple's products. You will work on infrastructure, MLOps, cloud and on-device deployment systems, and data engineering platforms that support our ML development lifecycle. You will be responsible for building and maintaining scalable machine learning infrastructure for training, evaluation, and deployment of computer vision and multimodal models. You will develop MLOps platforms and tools that streamline the ML development lifecycle from data ingestion to model deployment, create robust data pipelines for large-scale data collection, curation, preprocessing, and management, and implement on-device ML integration systems that deploy state-of-the-art algorithms to Apple devices. Working closely with ML algorithms engineers, data scientists, and quality assurance teams, you'll help deploy state-of-the-art computer vision technologies on Apple devices, balancing performance with the compute and power constraints of on-device inference. ## Related Videos - [Introduction to Azure Machine Learning](https://www.wearedevelopers.com/videos/368-introduction-to-azure-machine-learning) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [Harnessing Apple Intelligence: Live Coding with Swift for iOS](https://www.wearedevelopers.com/videos/1515-harnessing-apple-intelligence-live-coding-with-swift-for-ios) - [Docker build without Docker](https://www.wearedevelopers.com/videos/100114-docker-build-without-docker) - [DevOps Maturity Check – a way to balance autonomy and alignment](https://www.wearedevelopers.com/videos/58-devops-maturity-check-a-way-to-balance-autonomy-and-alignment) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Got AI ideas but no money? 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