Machine Learning Engineer, Strategic Data Solutions

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

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

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.