AIML - Sr. ML Engineer, NL Response Generation - Answers, Knowledge, & Info at Apple

Santa Clara, California, United States -

Full Time

Start Date

Immediate

Expiry Date

16 Dec, 25

Salary

0.0

Posted On

17 Sep, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, NLP, Deep Learning, Large Language Models, Software Engineering, Python, Go, C/C++, ML Frameworks, Personalization, User Behavior Modeling, Data-Driven Decision-Making, Critical Analysis, Prototyping, Evaluation, Algorithm Design

Industry

Computers and Electronics Manufacturing

Description

The Answers, Knowledge & Information team is revolutionizing the way hundreds of millions of people access information on their devices, all while keeping user privacy at the forefront. As an Applied ML team, we're pushing the boundaries of Apple Intelligence, result ranking, and innovative search technologies, all while running a low latency production service. Our work fuels intuitive information experiences across some of Apple's most iconic products, including Siri, Spotlight, Safari, Messages, Lookup, and more. Join us in shaping the future of how the world connects with information! We are looking for a senior Machine Learning Engineer with a passion for using machine learning to build intelligent search applications. Our team researches and implements novel query understanding, ranking and response generation techniques, machine learning algorithms and models that power amazing Search experiences across Apple products. DESCRIPTION This role will have the chance to work closely on Natural Language response generation models, make improvements and perform scalable evaluation that will impact Apple Users and broader AIML community. Role responsibilities include: - Contribute on research, design, implementation and evaluation of algorithms and models to enhance the quality and performance of personalized response generation models. - Use advanced NLP, deep learning and LLM techniques to generate grounded responses for user intent. - Analyze loss patterns in the current search and assistant stack and come up with insights, algorithms and techniques to resolve quality gaps with the goal of improving the top-line product metrics. - Develop a long-term technical vision; propose a roadmap for team setting clear objectives. - Collaborate with teams across the company to define product requirements and prioritize ranking criteria that optimize user satisfaction. - Establish metrics and continuously improve performance of models by applying innovative ML techniques. MINIMUM QUALIFICATIONS 4+ years Experience in Machine Learning, NLP and applying these techniques at scale Strong software engineering skills in mainstream programming languages, such as: Python, Go, C/C++ Strong communication skills Bachelors in Computer Science and industry work experience PREFERRED QUALIFICATIONS In-depth knowledge and expertise in applying Deep learning models, Large Language Models and their evaluations Extensive experience in building production quality systems or applications in search, recommendation systems, or information retrieval Experience using ML frameworks (pyTorch, JAX, TensorFlow, XGBoost etc.) Ability to quickly prototype ideas / solutions, and perform critical analysis Background in: personalization, user behavior modeling, and data-driven decision-making Advance degree (Master’s or Ph.D.) in Computer Science, Statistics, or related field, or equivalent industry work experience

Responsibilities

The role involves contributing to the research, design, implementation, and evaluation of algorithms and models for personalized response generation. The engineer will analyze loss patterns and develop a long-term technical vision to improve product metrics.