Senior GenAI & ML Engineer, Advanced Analytics

Apple, Inc.; Sunnyvale (CA); On-site; USD 185,000 - 325,000; Full time

Benefits offered by this job

Medical and dental coverage

Retirement benefits

Tuition reimbursement

Job summary

Apple, based in Sunnyvale, California, seeks an Applied Machine Learning Engineer focused on GenAI for Advanced Analytics within IS&T. You will design scalable ML models for demand forecasting, inventory optimization, and logistics planning in a complex enterprise setting.

Lead cross-functional efforts with engineering and data science teams, deploy models to production, and stay ahead of GenAI advances to drive high-impact projects across Apple’s supply chain.

Qualifications

• MS in Computer Science, Machine Learning, Applied Math or a related field.
• 5+ years of industry experience developing Machine Learning Solutions.
• Hands on experience in Python as programming language.
• Experience deploying ML solutions to production.

Responsibilities

• Design and develop advanced machine learning models, incl. Generative AI, for supply chain use cases.
• Collaborate with engineering, data science, and application teams to integrate analytics into enterprise systems.
• Stay updated on ML and GenAI advancements and identify ROI opportunities.
• Ensure analytics solutions are scalable across large enterprise environments.
• Plan multi-year GenAI strategy and drive high-ROI projects.
• Guide partner teams to enable analytics data strategy and infra for experimentation and deployment.
• Communicate results to partners and leaders to influence decisions.
• Mentor team members and contribute to analytics growth.

Skills

Python

GenAI

ML development

Production deployment

Education

MS in CS

PhD

Tools

TensorFlow

PyTorch

SQL

Spark

Cloud platforms

MLOps

Job description

Apple, based in Sunnyvale, California, seeks an Applied Machine Learning Engineer focused on GenAI for Advanced Analytics within IS&T. You will design scalable ML models for demand forecasting, inventory optimization, and logistics planning in a complex enterprise setting.

Lead cross-functional efforts with engineering and data science teams, deploy models to production, and stay ahead of GenAI advances to drive high-impact projects across Apple’s supply chain.