AIML - Senior Machine Learning Engineer, Siri and Information Intelligence

Cupertino,California,United States

Machine Learning and AI

As part of Apple Intelligence, Siri team is at the forefront of the next revolution in machine learning and NLP. Our innovative product redefines computing by leveraging cutting-edge technologies in Natural Language Understanding and Conversational AI. We are dedicated to creating groundbreaking conversational assistant technologies for both large-scale systems and new client devices, building upon our legacy of intelligent assistant solutions that already assist millions of users worldwide. We are seeking a highly skilled Senior Machine Learning Engineer specializing in NLP/Conversational AI to join our dynamic team. The ideal candidate will play a pivotal role in the evaluation and enhancement of our Apple Intelligence products. They will collaborate closely with cross-functional teams to implement and optimize models, ensuring the highest level of performance, accuracy, and scalability. This role offers an exciting opportunity to contribute to the advancement of AI systems and shape the future of computing. As a Machine Learning Engineer within the Siri team, you will define new approaches for evaluating state-of-the-art ML based systems, conversational AI, and model interpretability. You will collaborate with different modeling teams, and product managers to conduct thorough evaluation and analysis of Apple Intelligence products and models, identifying areas for improvement and optimization. You will work with large amounts of real-world data to analyze and propose changes to the Siri user experience. You will ensure data quality throughout all stages of acquisition and processing, data wrangling, etc. Your expertise in defining and measuring the online and offline end-to-end metrics will help communicate, evaluate, and iterate on state-of-the-art deployed models and predictors

Description

As Siri is becoming increasingly complex AI system, it is critical to understand the impact of each ML model on other dependent models, while assessing the impact on Siri end-user experience. The Siri team leads the development of advanced evaluation methodologies for ML based systems, model interpretability, and experimentation, to ensure that every release delivers an improved Siri user experience. The team is searching for talented ML Engineers to work with a passionate, product-focused team to define new approaches for evaluating ML based systems, conversational AI, and model interpretability You will run experiments, statistically interpret data with a mind on causation, data visualization, plus designing, building, and evaluating models. You will work with large amounts of real-world data to analyze and propose changes to Siri user experience. You will ensure data quality throughout all stages of acquisition and processing, data wrangling, etc. Your expertise in defining and measuring the online and offline end-to-end metrics will help communicate, evaluate, and iterate on state-of-the-art deployed models and predictors.

Minimum Qualifications

• 7+ years of professional work experience applying machine learning to real-world problems, and crafting scalable and effective data solutions.

• Strong domain knowledge in at least one of the following: NLP, conversational AI, speech recognition

• Excellent programming skills in Python and data analytical skills.

• Excellent problem solving, critical thinking, and communication skills.

Key Qualifications

Preferred Qualifications

• Strong attention to detail. Proven ability to dive into data to discover hidden patterns and conduct error/deviation analysis

• Good experience with applying Big Data tools (MapReduce, Hadoop, Hive and/or Pig, Spark) to large quantities of textual data

• Domain knowledge in applied statistics and experimental design is big plus!

• Enthusiasm for continuing to learn state-of-the-art techniques in machine learning/data science

• Strong background in A/B testing procedure, causal analysis, and cohort analysis.

• Exposure to model interpretability techniques and their real-world advantages/drawbacks

• Good Conversational AI domain knowledge

• Experience working with end-to-end pipelines and/or crowd-sourced data labeling

• B.S., M.S. or Ph.D. in Computer Science, Electrical Engineering, Statistics, Applied Math, Physics or related fields is preferred

Education & Experience

Additional Requirements

Pay & Benefits

• At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $175,800 and $312,200, and your base pay will depend on your skills, qualifications, experience, and location.Apple employees also have the opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple’s Employee Stock Purchase Plan. You’ll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses — including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation.Learn more (https://www.apple.com/careers/us/benefits.html) about Apple Benefits.Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

• Apple is an equal opportunity employer that is committed to inclusion and diversity. We take affirmative action to ensure equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics.Learn more about your EEO rights as an applicant. (https://www.eeoc.gov/sites/default/files/2023-06/22-088_EEOC_KnowYourRights6.12ScreenRdr.pdf)

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