Machine Learning Engineer, Sales Engineering

Apple’s Sales Engineering Rapid Application Development (RAD) team is hiring a Machine Learning Engineer in Sales Engineering to design and deploy scalable machine learning and generative AI systems for Apple’s global Channel Sales ecosystem.

Responsibilities

• Design, build, and deploy scalable machine learning and generative AI solutions for Apple’s global Channel Sales ecosystem
• Develop and optimize ML pipelines using LLMs, LMMs, and RAG-based architectures for production-grade applications
• Collaborate with cross-functional teams to translate business needs into intelligent, data-driven systems and workflows
• Fine-tune and evaluate transformer-based models such as GPT, LLaMA, and BERT for accuracy, performance, and scalability
• Prototype and productionize emerging AI capabilities, including agentic workflows and generative assistants
• Apply MLOps best practices across training, deployment, monitoring, and continuous improvement
• Ensure secure and compliant handling of sensitive data, including PII, aligned with Apple’s privacy standards

Requirements

• Proven ability to fine-tune, adapt, and deploy LLMs/LMMs into real-world, production-grade applications
• Proficiency in Python and leading ML frameworks including PyTorch and TensorFlow
• Hands-on experience with Hugging Face Transformers and associated libraries
• Solid understanding of Retrieval-Augmented Generation (RAG) and experience with orchestration frameworks such as LangChain or LlamaIndex
• Familiarity with distributed computing, cloud platforms (AWS, GCP, Azure), and containerization/orchestration tools (Docker, Kubernetes)
• Exceptional problem-solving skills, with the ability to clearly articulate complex ML/AI concepts 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 to support 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 optimizing transformer-based architectures such as BERT, GPT, and LLaMA for low latency and high-performance inference
• Demonstrated ability to communicate technical results and ML/LLM concepts with clarity and impact to both technical and non-technical stakeholders
• Experience applying ML methodologies in specific domains, including sales

Minimum Qualifications

• MS / BS in Computer Science, Machine Learning, Artificial Intelligence, or a closely related technical field, or equivalent experience
• 5+ years experience developing and deploying machine learning solutions with a strong focus on LLMs or LMMs
• 5+ years experience with LLMs and transformer-based architectures (for example, BERT, GPT, LLaMA)

Technologies

• Python
• PyTorch
• TensorFlow
• Hugging Face Transformers
• LangChain
• LlamaIndex
• LLMs
• LMMs
• RAG
• GPT
• LLaMA
• BERT
• Transformer-based architectures
• Docker
• Kubernetes
• AWS
• GCP
• Azure

Location: Austin, TX (onsite)