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Apple Machine Learning Engineer- Advanced Analytics United States, California, Sunnyvale 423174068
25.03.2025
Description
Key responsibilities include:• 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, identity 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.
Minimum Qualifications
- PhD/MS in Computer Science, ML, Applied Math or a related field. 10+ years of industry experience developing data science solution 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) to solve impactful real world problems
- Expert practical knowledge of algorithms (eg: 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.
Preferred Qualifications
- 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.
Pay & Benefits
- At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $207,800 and $312,200, and your base pay will depend on your skills, qualifications, experience, and location.Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
Apple is an equal opportunity employer that is committed to inclusion and diversity. We take affirmative action to ensure equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics.
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