Apple · Cupertino

AIML - Machine Learning, Siri Comprehension & Planning

(f/m/d) · 1/24/2025

Description

As a machine learning engineer on the team, you will play a key role in the team’s impact and development. You will have responsibilities ranging from machine learning for data exploration, advanced statistical modeling, tuning and adapting deep learning models, and evaluating their performance. You’ll also design and maintain intricate data ingestion and correction frameworks to capitalize on Siri’s vast data repository. You will apply innovative machine learning methods and statistical analysis to continually advance Siri’s capabilities. As a machine learning engineer on the team, you will play a key role in the team’s impact and development. You will have responsibilities ranging from machine learning for data exploration, advanced statistical modeling, tuning and adapting deep learning models, and evaluating their performance. You’ll also design and maintain intricate data ingestion and correction frameworks to capitalize on Siri’s vast data repository. You will apply innovative machine learning methods and statistical analysis to continually advance Siri’s capabilities. At Apple, you will work closely with diverse, cross-functional teams spanning software, research, and product development. You will play a key role in shaping system architecture, designing data-processing pipelines, evaluating model performance, and participating in code reviews. The ideal candidate will possess a strong passion for applied machine learning, top-notch software engineering skills, and a drive to deliver results. Our team is at the forefront of cutting-edge machine learning technology, constantly striving to create exceptional products for our customers. If this opportunity excites you, we look forward to receiving your application.

Qualifications

  • Hands on experience with handling large datasets and creating data processing pipelines.
  • Hands-on experience developing end to end machine learning systems: defining and creating metrics and datasets, training models and performing error triage
  • Strong background in Python development and experience using Python for data science work.
  • Proficiency in data processing frameworks (Numpy / Pandas)
  • Excellent communication: strong interpersonal, verbal and written skills
  • Masters or PhD in Computer Science, Machine Learning Engineering or equivalent professional experience

Preferred Qualifications

  • Experience creating and maintaining large scale, robust machine learning processes for use in a multi-person team
  • Experience shipping and improving machine learning models in a production environment
  • Experience developing data analytics pipelines for natural language understanding or digital assistants

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 $143,100 and $264,200, 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 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.

Application

View listing at origin and apply!
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