Senior / Staff ML Engineer, Apple Cloud AI Platform at Apple

Cupertino, California, United States -

Full Time

Start Date

Immediate

Expiry Date

21 May, 26

Salary

0.0

Posted On

20 Feb, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Full-Stack Engineering, Data Platforms, ML Platforms, Backend Systems, Applied AI, Python, Spark, Ray, gRPC, GraphQL, REST, Kafka, Cloud Environments, Distributed Systems, CI/CD Pipelines, ML Lifecycle

Industry

Computers and Electronics Manufacturing

Description

Apple Cloud AI Platform powers the machine learning, AI, and data systems that enable intelligent experiences across Apple consumer products. We are looking for a Software Engineer who is excited to work directly with Apple product teams and translate real-world AI needs into production-ready solutions. You will operate at the intersection of full-stack engineering, data and ML platforms, backend systems and applied AI, using customer requirements to build end-to-end solutions and workflows as part of our platform offerings. This role is ideal for engineers who are highly collaborative, proactive, adaptable, and capable of turning ambiguous customer requests into working AI-powered solutions at scale. DESCRIPTION In this role you will partner directly with internal customers to understand their use cases, evaluate technical requirements, and build AI-driven systems and solutions that leverage Apple Cloud AI Platform capabilities. You will work across the stack, from data ingestion to model execution to UI integration, without strict constraints on programming languages or frameworks. You will prototype quickly, harden solutions for production, build services and feed insights back to platform teams to influence roadmap and improve the developer experience. You will also act as a bridge between product management, partner platform, and customer teams by helping define best practices, documenting patterns, and working closely with platform engineering groups to drive alignment and deliver systems. Success in this role requires a combination of strong engineering fundamentals, applied ML awareness, platform thinking, customer empathy, and the ability to deliver in fast-evolving environments. MINIMUM QUALIFICATIONS 7+ years of industry experience building production systems, full-stack applications, data workflows, ML powered products, or platform tooling. Experience leading cross-team engineering efforts or customer-facing technical engagements. Experience with modern AI and data stack (Python and at least some of: Spark, Ray, gRPC, GraphQL, REST, Kafka or similar). Experience with cloud environments, distributed systems, containers, and CI/CD pipelines. Familiarity with ML lifecycle concepts: experiment tracking, model packaging, deployment strategies, evaluation, and data governance. Strong communication skills with customer empathy and ability to drive alignment. Comfortable working in ambiguous environments with high ownership expectations. BS, MS, or PhD in Computer Science, Software Engineering, Machine Learning, or equivalent degree with applicable experience PREFERRED QUALIFICATIONS Build prototypes, demos, and reference implementations to accelerate platform adoption. Influence platform roadmap based on customer lifecycle needs (developer experience, scale, reliability, governance, ML metadata). Experience enabling advanced ML workflows such as distributed training, tuning, feedback loops, observability, and evaluation pipelines. Experience across multiple languages and execution environments and ability to select appropriate tools. Experience with ML frameworks such as PyTorch or TensorFlow. Experience with modern frontend frameworks such as React. Experience building developer platforms (SDKs, developer tools, agents, internal platforms). Ability to represent customer needs to platform engineering and drive cross-team technical direction.

Responsibilities

This role involves partnering directly with internal customers to understand their use cases, evaluate technical requirements, and build AI-driven systems leveraging the Apple Cloud AI Platform capabilities. The engineer will work across the stack, from data ingestion to model execution to UI integration, prototyping solutions and feeding insights back to platform teams.