Machine Learning Engineer - Strategic Data Solutions at Apple

Austin, Texas, United States -

Full Time

Start Date

Immediate

Expiry Date

01 Jul, 26

Salary

0.0

Posted On

02 Apr, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Optimization, Data Science, Python, SQL, Collaboration, Communication, Problem Solving, Data Pipelines, Decisioning, Reporting, Stakeholder Engagement, Technical Solutions, Emerging Technologies, Operations Research, Mathematical Optimization

Industry

Computers and Electronics Manufacturing

Description

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 thatʼs constantly learning and having fun while solving tough business problems? Weʼd 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, 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 Create reporting and monitor decisioning quality to maintain operational and business metric health Build end-to-end data pipelines and models to automate and improve fulfillment processes. Productionize and own the stack 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, Political Science, Biology, etc) or Bachelorʼs degree with equivalent experience At least 3 years of practical experience (acquired through work, independent projects, or academic research) in deploying machine learning 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 Effective communication skills to translate complex concepts and analysis into concise, business- focused solutions Team-oriented skills and values to facilitate effective collaboration with business and technical partners PREFERRED QUALIFICATIONS PhD in a related field (e.g., Computer Science, Statistics, Operations Research, or similar) Experience with 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 Experience with AI-assisted coding tools

Responsibilities

As a Machine Learning Engineer, you will engage with stakeholders to translate business problems into technical solutions and design data-driven solutions. You will collaborate with partners to implement decisioning in production and build end-to-end data pipelines to improve fulfillment processes.