Summary

Apple is where individual imaginations gather together, committing to the values that lead to great work. It’s the diversity of our people and their thinking that inspires the innovation that runs through everything we do. Here, you’ll do more than join something, you’ll add something.

Description

We are looking for a versatile Machine Learning Engineer / Next-Generation Data Scientist who can own the full lifecycle of intelligent solutions—from problem framing and data sourcing through to model development, deployment, and user-facing delivery.

With the acceleration of AI-assisted coding, we are seeking someone who can operate as a full-stack problem solver, leveraging machine learning, advanced analytics, and modern development tooling to rapidly build scalable, production-ready solutions.

You will work at the intersection of data, AI, and engineering—transforming complex operational and business challenges into impactful, deployable products. This role is ideal for someone who thrives in ambiguity, embraces new tools, and is motivated by delivering real-world outcomes rather than just models.

Responsibilities

• Own end-to-end solution delivery: from problem definition through to deployed product
• Engage with stakeholders to understand business problems and translate them into analytical solutions
• Identify, source, and engineer relevant datasets (structured and unstructured)
• Leverage modern AI tools (e.g. code generation, copilots) to accelerate development across the stack
• Build lightweight front-end applications or interfaces to expose models and insights
• Deploy solutions into production environments (cloud or on-prem) with scalability and reliability in mind
• Ensure solutions are robust, reusable, and aligned with engineering best practices
• Collaborate across data science, engineering, and operations teams to embed solutions into workflows
• Stay current with emerging AI, ML, and tooling trends, and identify opportunities to leverage them
  
  

Minimum Qualifications

• 5+ years of experience in data science or machine learning, preferably within supply chain, operations, or a related domain.
• Proficiency in programming (e.g. Python) and experience with modern ML frameworks
• Experience using or willingness to adopt AI-assisted development tools (e.g. code generation, LLM-based tooling)
• Ability to work across the full technology stack (data pipelines, modelling, APIs, basic front-end)
• Understanding of software engineering principles (version control, testing, modular design)
• Familiarity with cloud platforms (e.g. AWS) and deployment patterns
• Strong problem-solving skills with the ability to operate in ambiguous environments
• Excellent communication skills, with the ability to explain technical concepts to non-technical stakeholders