Machine Learning Engineer, Sales Engineering

Apple

3h

About The Position

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.

Requirements

• 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).

Nice To Haves

• 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.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level