AIML - Senior Machine Learning Engineer, NLP - Siri and Information Intelligence

Key Skills

Aartificial intelligence, Apache Pig, Big Data Technology, Effective communication skills, Information Intelligence, Machine learning techniques, MapReduce, Natural Language Processing (NLP), SPARK Programming

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

Preferred Qualifications

• 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
• Good experience with applying Big Data tools (MapReduce, Hadoop, Hive and/or Pig, Spark) to large quantities of textual data
• Excellent problem solving, critical thinking, and communication skills.
• 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
• Education
• B.S., M.S. or Ph.D. in Computer Science, Electrical Engineering, Statistics, Applied Math, Physics or related fields is preferred.

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 $166,600 and $296,300, 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 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.