Senior Machine Learning Engineer, Natural Language Generation

From our origins in iPhone keyboard input, the Input Experience NLP team has

expanded to a broad charter: improve the user experience with robust language

understanding and personalized text composition, across languages and Apple

platforms. We build the ML models that underlie Summarization, Smart Reply,

Writing Tools, and other features deeply integrated into Apple products.

Generative AI is a transformative technology that we have only just begun to

incorporate into our digital lives, to help everyday people digest the deluge of

information they receive and express themselves more clearly. On our team, you

will help build the future and have a voice in the shape it takes. We are

looking for a Senior Machine Learning Engineer to own the model quality of

Summarization and other core Apple Intelligence features. You will develop the

next generation of our ML models, so that they better serve the full range of

our customers, across languages, writing styles, and other personal context, in

a privacy-preserving way and to Apple’s high standards of quality. You will

design the architecture of the modeling pipelines that define our slice of Apple

Intelligence, driving the direction of our team’s efforts to produce user

experiences that feel magical. You will join an ambitious, organized, and

collaborative team. We’re in a unique position to integrate the latest

innovations from the ML community and work on features that reach everyday

users, including your family and friends. You’ll work closely with other teams

across Apple, collaborating on human interfaces, user studies,

internationalization, ML technologies, system integration, and more. 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. That happens because every one of us shares a belief that we can make

something wonderful and share it with the world, changing lives for the better.

It’s the diversity of our people and their thinking that inspires the innovation

that runs through everything we do. When we bring everybody in, we can do the

best work of our lives. Here, you’ll do more than join something—you’ll add

something.

DESCRIPTION

As a Senior Machine Learning Engineer on our team, you will be responsible for

the definition, design, and quality of increasingly sophisticated AI features

that ship to a global audience. You will drive the development of workflows that

facilitate efficient data synthesis, data curation, prompt engineering, and

model evaluation. Finally, you will contribute to a company-wide effort to build

robust modeling processes that optimize our ability to iterate rapidly and

continuously deliver improvements to our customers. Key responsibilities: * Own

the model quality of shipping and unreleased Apple Intelligence features *

Prioritize and drive modeling efforts across multiple fronts * Analyze user

feedback to understand shortcomings of our models and evaluation data * Define

robust evaluation mechanisms to drive data curation, metric calibration, and

model hill-climbing * Research state-of-the-art SFT/PEFT/RLHF/distillation

techniques for improving model quality and robustness * Implement pipelines,

experiments, and simulations to assess the value of modeling changes

MINIMUM QUALIFICATIONS

MS or PhD in Computer Science or related field, or equivalent practical

experience History of shipping AI features built on language models Experience

building and maintaining model pipelines end-to-end, from data

curation/synthesis and LLM judges to post-training Strong Python programming

skills, with experience developing production-quality Python modules Excellent

written and verbal communication skills

PREFERRED QUALIFICATIONS

History of driving cross-functional collaborations and leading technical efforts

Expertise deploying models on-device, reasoning about latency, activation size,

quantization, and distillation Background in linguistics, fluency in multiple

languages, or experience scaling NLP features for global audiences