About the role
Summary
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. Apple is where individual imaginations gather together, committing to the values that lead to great work. Every new product we build, service we create, or Apple Store experience we deliver is the result of us making each other’s ideas stronger. Apple’s Sales Engineering team is shaping the future of Channel Sales with innovative, high-impact applications. We’re looking for a Machine Learning Engineer to help us design and build the next generation of intelligent systems that power Apple’s global partner ecosystem. In this role, you’ll develop and deploy machine learning solutions while leveraging generative AI and advanced ML capabilities to deliver scalable, production-ready systems that accelerate strategic, high-impact initiatives across Apple Channel Sales. If you’re passionate about applying AI to solve complex business problems, experimenting with emerging GenAI technologies, and building products that make a real difference, join our collaborative team and help us move fast on game-changing ideas.
Description
Apple’s Sales Engineering Rapid Application Development (RAD) team is looking for a Machine Learning Engineer to build intelligent, scalable solutions that power Apple’s global Channel Sales. You’ll leverage generative AI and advanced machine learning technologies to deliver high-performance, production-ready systems that drive measurable business impact. The ideal candidate blends deep ML expertise with strong engineering skills, is passionate about applying AI to solve real-world problems, and thrives in fast-paced environments delivering value quickly. You’ll work side by side with product, design, and engineering teams to design, train, deploy, and optimize ML-powered applications that push the boundaries of innovation—whether enabling GenAI-driven workflows, implementing RAG-based systems, or pioneering new intelligent capabilities. If you’re excited about shaping impactful AI solutions in a collaborative, experiment-driven environment, Sales Engineering RAD team is where you’ll thrive.
Minimum Qualifications
M.S. in Computer Science, Machine Learning, Artificial Intelligence, or a closely related technical field, or equivalent practical experience. 5+ years experience developing and deploying machine learning solutions, with a strong focus on Large Language Models (LLMs) or Large Multimodal Models (LMMs). 5+ years experience with LLMs and transformer-based architectures (e.g., BERT, GPT, LLaMA).
Preferred Qualifications
Proven ability to fine-tune, adapt, and deploy LLMs/LMMs into real-world, production-grade applications. Proficiency in Python and leading ML frameworks such as PyTorch and TensorFlow. Hands-on experience leveraging Hugging Face Transformers and associated libraries. Solid understanding of Retrieval-Augmented Generation (RAG) and practical experience with orchestration frameworks like LangChain or LlamaIndex. Familiarity with distributed computing, cloud platforms (AWS, GCP, Azure), and containerization/orchestration tools (Docker, Kubernetes). Exceptional problem-solving skills and the ability to articulate complex ML/AI concepts clearly and effectively to diverse audiences. Experience extending beyond traditional LLMs/LMMs to include agent-based systems and agentic workflows. Proficiency with advanced LLM serving and inference frameworks, ensuring scalable and efficient model deployment. Practical experience building sophisticated RAG applications and orchestrating complex LLM pipelines from inception to deployment. Working knowledge of distributed systems and cloud-native infrastructure. Expertise in optimizing transformer-based architectures (e.g., BERT, GPT, LLaMA) for low-latency, high-performance inference. Demonstrated ability to communicate complex technical results and ML/LLM concepts with clarity and impact to both technical and non-technical stakeholders. Experience applying ML methodologies in specific domains, such as sales.
Skills & Tags
Aplyr's read
Apple is a tech giant known for its sleek design and innovation, attracting top talent in engineering, design, and business operations.
What's promising
- •Apple consistently leads in tech innovation with a strong focus on design and user experience.
- •The company's global brand recognition offers employees a prestigious platform for career growth.
- •Apple's robust ecosystem integrates hardware, software, and services, creating diverse job opportunities.
What to watch
- •High-pressure work environment with demanding deadlines can impact work-life balance.
- •Apple's secretive culture may limit transparency and cross-departmental communication.
- •Dependence on hardware sales makes the company vulnerable to market saturation risks.
Why Apple
- •Apple's design philosophy emphasizes simplicity and elegance, setting it apart in the tech industry.
- •The company has a unique retail presence with its own stores enhancing customer experience.
- •Apple's closed ecosystem creates a seamless integration across its products, unmatched by competitors.
Aplyr’s read is generated by AI from public sources. Was it useful?
About Apple
Apple Inc. is a leading technology company known for its innovative consumer electronics, software, and services. The company designs and manufactures products such as the iPhone, iPad, Mac computers, and wearables, significantly influencing the tech industry and consumer behavior worldwide.
Similar roles
Sr SW Engineer, Machine Learning
Roku
Lead Machine Learning Engineer - LMTS
Salesforce
Associate Applied AI Engineer (Benelux) - Orbit Program
Celonis
Machine Learning Engineer, Next-Generation Recommendation Systems (New Grad / PhD)
Unity Technologies
Machine Learning Engineer, Next-Generation Recommendation Systems (New Grad / PhD)
Unity Technologies
Machine Learning Engineer, Next-Generation Recommendation Systems (New Grad / PhD)
Unity Technologies