About the role
AI summarisedMachine Learning Engineer on Apple's Fulfillment Operations team, applying ML and optimization to global supply chain logistics problems. The role involves designing, building, deploying, and maintaining end-to-end solutions that improve operational efficiency and security.
TechnologyFull-timeSupport and Service
Key Responsibilities
- 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
Requirements
- 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
- 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