Machine Learning Engineer- Advanced Analytics, Worldwide Business Process Re-Engineering

Full-time - Senior

Sunnyvale, CA

Computer and Electronic Product Manufacturing

About the position

Apple is looking for a dynamic, highly motivated, experienced Applied Machine Learning Engineer, with expertise and experience in GenAI, for the Advanced Analytics team to join the WW Business Process Re-Engineering Org within Worldwide Sales and Operations Support. This role is focused on applying GenAI technologies to solve complex supply chain challenges within an enterprise context. The ideal candidate will have a proven track record of delivering scalable, value-driven data science and GenAI solutions. You will be working with a team of experts responsible for designing and developing advanced data science solutions from strategic to executional decision-making and with engineering and application teams to integrate these solutions into our existing systems.

Responsibilities

• Design and develop advanced machine learning models, particularly focusing on Generative AI, to address specific supply chain use cases such as demand forecasting, inventory optimization, and logistics planning.
• Work closely with cross-functional teams, including engineering, data science, and application development, to integrate GenAI solutions into enterprise systems.
• Stay abreast of the latest advancements in machine learning and GenAI, and explore innovative ways to apply these technologies to supply chain challenges.
• Ensure that GenAI solutions are scalable and can be deployed across large, complex enterprise environments.
• Think big about the arc of development of GenAI over multi year horizon, identify high ROI opportunities that will benefit from this technology and deliver critical projects.
• Guide partner teams to enable analytics data strategy and infra to support experimentation as well as robust deployment at enterprise scale.
• Communicate results and insights to partners and senior leaders, technical and non-technical.
• Influence decision making with leadership.
• Provide guidance and mentorship to team members and contribute to the overall growth of the analytics team.

Requirements

• PhD/MS in Computer Science, ML, Applied Math or a related field.
• 10+ years of industry experience developing data science solutions with 2+ years leveraging GenAI.
• Experience prototyping, developing software and implementing data science pipelines and applications in programming languages (Python/C++/TensorFlow, PyTorch, and other relevant ML frameworks).
• Expert practical knowledge of algorithms (e.g., anomaly detection, NLP, Deep learning, Tensor Flow, LLM), and strong sense of levers impacting accuracy.
• Strong understanding of deep learning architectures, particularly those relevant to Generative AI (e.g., GANs, VAEs).
• Expert understanding of data frameworks (Spark, graph db), infrastructure, and engineering needs including cloud platforms for deploying data science solutions.
• Experience deploying GenAI solutions in operational context successfully.
• Familiarity with autonomous agents for solving real world problems.
• Experience defining and measuring KPI related to the success of AI implementations.

Nice-to-haves

• Experience with reinforcement learning and its applications in supply chain optimization.
• Knowledge of natural language processing (NLP) and its use in supply chain analytics.
• Familiarity with DevOps practices and CI/CD pipelines for machine learning models.
• Experience in the application of data science within an Operational or Supply Chain context.
• Innate curiosity and bias for action with expert ability to identify, define and complete project plans.
• Proven history of designing, developing and deploying impactful analytical solutions at scale.
• Self-sufficient with an ability to thrive in an environment of autonomy amidst ambiguity.
• Expert capability to work with global multi-functional teams.
• Sound communication skills - adept at messaging domain and technical content, at a level appropriate for the audience.
• Strong ability to gain trust with stakeholders and senior leadership.
• Phenomenal team leader - invested in the collective success of the team and project outcomes.

Benefits

• Comprehensive medical and dental coverage.
• Retirement benefits.
• A range of discounted products and free services.
• Reimbursement for certain educational expenses - including tuition.
• Opportunity to participate in Apple's discretionary employee stock programs.
• Eligibility for discretionary restricted stock unit awards.
• Ability to purchase Apple stock at a discount through Employee Stock Purchase Plan.
• Potential for discretionary bonuses or commission payments.
• Relocation assistance.