Machine Learning Engineer, Strategic Data Solutions

Apple, Inc.; Singapore; In loco; SGD 100.000 - 180.000; Tempo pieno

Descrizione del lavoro

Apple, Inc. is seeking a Machine Learning Engineer for Strategic Data Solutions to optimize fulfillment operations through data-driven methods. You will build end-to-end ML and optimization solutions, from data pipelines to deployment, impacting global supply chain efficiency.

You will collaborate with partners across Apple, delivering robust, scalable systems and sharing insights to advance technical capabilities within the team.

Competenze

• Graduate degree with research/work experience utilizing data science techniques (CS, Statistics) or Bachelor's with equivalent experience.
• At least 3 years of practical experience building and deploying programmatic solutions.
• Proficiency in Python or a similar programming language.
• Theoretical understanding of machine learning algorithms and their strengths/weaknesses.
• Ability to use SQL to extract insights from data.
• Experience with version control and modern development workflows.

Mansioni

• Engage with stakeholders to translate business problems into technical solutions.
• Design data-driven solutions balancing established techniques with custom approaches.
• Collaborate to implement real-time and batch decisioning in production.
• Build and maintain data pipelines and distributed systems powering fulfillment operations.
• Write clean, testable code and establish best practices for reliability.
• Communicate with stakeholders across different technical backgrounds.

Conoscenze

Python

SQL

Data pipelines

Machine learning

Version control

Collaboration

Problem solving

Communication

Formazione

Graduate degree in CS/Statistics/Data Science

Bachelor’s degree

Strumenti

Git

Docker

Descrizione del lavoro

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 solutionsDesign data-driven solutions, balancing established techniques with custom approaches where they add valueCollaborate with technical partners to implement robust real-time and batch decisioning in productionBuild and maintain data pipelines, distributed systems, and infrastructure that power fulfillment operationsWrite clean, testable, maintainable code and establish best practices for code quality and system reliabilityCreate reporting and monitor decisioning quality to maintain operational and business metric healthCommunicate with stakeholders with varying technical backgrounds and business priorities about your workShare 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.

Apple is an equal opportunity employer that is committed to inclusion and diversity. Apple provides reasonable accommodations to applicants with disabilities and in accordance with local requirements. Apple is a drug-free workplace.

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