Machine Learning Engineer, Strategic Data Solutions
May 28, 2026 Singapore
About us
Working at Apple means doing more than you ever thought possible and having more impact than you ever imagined.
- Size: 10,000+ employees
- Industry: Technology
Do you love the challenge of solving complex problems that can have a direct and meaningful impact on the company? Do you want to be part of a supportive team that's constantly learning and having fun while solving tough business problems? We'd love to talk to you if you do!
Strategic Data Solutions empowers internal partners and optimizes the customer experience by delivering data-driven solutions across Apple - from fraud mitigation and security to supply chain optimization and fulfillment. This role is on our Fulfillment Operations team, where the enormous scale and complexity of Apple's global supply chain present exciting opportunities for applying machine learning and optimization to real-world logistics problems.
As a Machine Learning Engineer on this team, you will work with partners across Apple, sometimes using machine learning and optimization techniques to design, build, deploy, and maintain end-to-end solutions that improve operational efficiency and security, with a direct, measurable impact on the company and our customers.
Our commitment to you: We will provide challenging problems that will engage your curiosity. We will provide an organizational culture that values collaboration, problem-solving, and work-life balance. We will provide mentorship to further develop your technical and leadership skills.
Description
Engage with stakeholders to translate ambiguous business problems into technical solutions
Design data-driven solutions, balancing established techniques with custom approaches where they add value
Collaborate with technical partners to implement robust real-time and batch decisioning in production
Build and maintain data pipelines, distributed systems, and infrastructure that power fulfillment operations
Write clean, testable, maintainable code and establish best practices for code quality and system reliability
Create reporting and monitor decisioning quality to maintain operational and business metric health
Communicate with stakeholders with varying technical backgrounds and business priorities about your work
Share what you're learning about emerging technologies and methods to improve your team's overall technical capabilities
Preferred Qualifications
PhD in a related field (e.g., Computer Science, Statistics, Operations Research, or similar)
4+ years of practical experience building solutions at scale in Python or another programming language.
Experience with fulfillment operations, supply chain, operations research or mathematical optimization techniques (e.g., linear programming).
Demonstrate ability to think holistically about system structures and interactions in order to anticipate technical, business, and customer impact.
Solid grasp of computer science fundamentals including data structures and algorithms.
Building technical solutions by using machine learning techniques a plus.
Experience with AI-assisted coding tools.
Minimum Qualifications
Graduate degree with research/work experience utilizing data science techniques (including but not limited to Computer Science, Statistics, etc) or Bachelor's degree with equivalent experience
At least 3 years of practical experience (acquired through work, independent projects, or academic research) in building and deploying programmatic solutions to answer real-world questions
Practical experience implementing data science applications in Python or a similar programming language
Theoretical understanding of machine learning algorithms and their relative strengths and weaknesses
Ability to use a querying language such as SQL to extract insights from data
Experience working with version control systems and modern development workflows
Team-oriented skills and values to facilitate effective collaboration with business and technical partners
Excellent problem solving, critical thinking, and communication skills to translate complex concepts and analysis into concise, business-focused solutions
Self-motivated, proactive, fast learner and solution-oriented
Strategic Data Solutions empowers internal partners and optimizes the customer experience by delivering data-driven solutions across Apple - from fraud mitigation and security to supply chain optimization and fulfillment. This role is on our Fulfillment Operations team, where the enormous scale and complexity of Apple's global supply chain present exciting opportunities for applying machine learning and optimization to real-world logistics problems.
As a Machine Learning Engineer on this team, you will work with partners across Apple, sometimes using machine learning and optimization techniques to design, build, deploy, and maintain end-to-end solutions that improve operational efficiency and security, with a direct, measurable impact on the company and our customers.
Our commitment to you: We will provide challenging problems that will engage your curiosity. We will provide an organizational culture that values collaboration, problem-solving, and work-life balance. We will provide mentorship to further develop your technical and leadership skills.
Description
Engage with stakeholders to translate ambiguous business problems into technical solutions
Design data-driven solutions, balancing established techniques with custom approaches where they add value
Collaborate with technical partners to implement robust real-time and batch decisioning in production
Build and maintain data pipelines, distributed systems, and infrastructure that power fulfillment operations
Write clean, testable, maintainable code and establish best practices for code quality and system reliability
Create reporting and monitor decisioning quality to maintain operational and business metric health
Communicate with stakeholders with varying technical backgrounds and business priorities about your work
Share what you're learning about emerging technologies and methods to improve your team's overall technical capabilities
Preferred Qualifications
PhD in a related field (e.g., Computer Science, Statistics, Operations Research, or similar)
4+ years of practical experience building solutions at scale in Python or another programming language.
Experience with fulfillment operations, supply chain, operations research or mathematical optimization techniques (e.g., linear programming).
Demonstrate ability to think holistically about system structures and interactions in order to anticipate technical, business, and customer impact.
Solid grasp of computer science fundamentals including data structures and algorithms.
Building technical solutions by using machine learning techniques a plus.
Experience with AI-assisted coding tools.
Minimum Qualifications
Graduate degree with research/work experience utilizing data science techniques (including but not limited to Computer Science, Statistics, etc) or Bachelor's degree with equivalent experience
At least 3 years of practical experience (acquired through work, independent projects, or academic research) in building and deploying programmatic solutions to answer real-world questions
Practical experience implementing data science applications in Python or a similar programming language
Theoretical understanding of machine learning algorithms and their relative strengths and weaknesses
Ability to use a querying language such as SQL to extract insights from data
Experience working with version control systems and modern development workflows
Team-oriented skills and values to facilitate effective collaboration with business and technical partners
Excellent problem solving, critical thinking, and communication skills to translate complex concepts and analysis into concise, business-focused solutions
Self-motivated, proactive, fast learner and solution-oriented
Additional Information
- Posted: May 28, 2026