Embedded Machine Learning Internship Jobs in Santa Clara, CA

Imagine what you could do here. At Apple, great ideas have a way of becoming great products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish.
Are you an enthusiastic Machine Learning Engineer eager to apply your expertise in a fast-paced, innovative tech environment? Join our Global Sourcing & Supply Management (GSSM) Solutions team as a key player in revolutionizing our supply chain.
As a Machine Learning Engineer on our core AI/ML team, you will design and build GenAI-powered features and workflows leveraging LLMs and modern AI techniques. You will collaborate closely with business stakeholders, product teams, and data engineers to translate complex challenges into practical AI/ML solutions and effectively communicate insights to senior management. Your work will empower data-driven decision-making, optimize workflows, and drive measurable impact across the supply chain.
If you thrive in a collaborative environment, are passionate about applying AI/ML to solve real-world business problems, and are excited to work with cutting-edge GenAI technologies, we want to hear from you!
Description
- Partner with business and product teams to identify high-impact opportunities and translate ambiguous requirements into GenAI-powered features and workflows delivered through a shared AI platform and embedded across products
- Design, build, and own end-to-end GenAI capabilities that support both a centralized AI platform and product teams, covering all aspects from prompt and tool design to agent orchestration, retrieval strategies, model selection, and system evaluation
- Develop reliable, scalable, and cost-aware GenAI features in collaboration with platform, data, and application engineering teams, ensuring strong performance, observability, and maintainability in production environments
- Establish evaluation and monitoring strategies for GenAI-driven features, focusing on output quality, correctness, safety, and business relevance through offline benchmarks, automated checks, and human-in-the-loop review
- Develop Text-to-SQL and structured reasoning capabilities that enable natural-language interaction with structured data, ensuring accuracy, security, and alignment with business semantics
- Leverage agentic AI patterns (multi-step reasoning, tool use, planning, memory, feedback loops) to support complex workflows, while establishing guardrails for reliable and predictable behavior
- Communicate trade-offs, system behavior, and limitations clearly to technical and non-technical stakeholders, enabling informed product and business decisions
- Continuously research, prototype, and operationalize emerging GenAI techniques to improve platform capabilities and accelerate adoption across teams
Preferred Qualifications
Strong problem-solving skills and the ability to tackle ambiguous, real-world challenges, along with clear communication and collaboration skills
Experience with modern deep learning frameworks, such as PyTorch or TensorFlow
Hands-on experience working with transformer-based models, including large language models (e.g., GPT style models or BERT-like architectures)
Practical experience leveraging LLMs or GenAI models via APIs to create reliable and user-facing features or workflows
Familiarity with common GenAI tools and frameworks, such as LangChain or similar, with the ability to learn and adapt as the ecosystem evolves
Solid understanding of foundational ML concepts including supervised, unsupervised and reinforcement learning
Solid understanding of core machine learning concepts, including supervised and unsupervised learning; exposure to reinforcement learning is a plus
Experience with model deployment pipelines and serving GenAI models in production
Experience applying modern ML or GenAI techniques in production workflows, including tasks such as Retrieval-Augmented Generation (RAG), structured reasoning, or prompt-based system design
Experience working in Supply Chain, Operations, or a related field
Ability to operate independently and lead without authority
Minimum Qualifications
Bachelors degree
PhD/MS in Computer Science, Statistics, Applied Math or a related field
3+ years of industry experience
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 $150,400 and $225,300, and your base pay will depend on your skills, qualifications, experience, and location.
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.