Senior Machine Learning Engineer - Maps Services Evaluation

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! Maps Evaluation team is looking for a senior machine Learning engineer to help develop the next generation of Maps Evaluation techniques and tools, to evaluate Maps ML-based systems and features. The engineering position is a role suited for candidates who enjoy approaching a variety of problems with small teams to make an outsized impact on Apple products. The ideal candidate will have experience building and evaluating search and recommendation systems, NLP systems, and/or GenAI features. Research experience in ML is highly preferred.
As a ML engineer on the Maps Evaluation team, you have the opportunity to build AI-based techniques and tools to bring the quality of Maps ML-based systems to the next level. You will also be deeply involved in evaluating the GenAI based Maps features. You will work closely with PMs, machine learning engineers and scientists, developers, statisticians and other evaluation engineers to improve a core product that touches millions of users worldwide every single day.
  • 5+ years of software development experience with at least one major language such as Java or Python
  • 5+ years of experience in designing and evaluating search or recommendation systems
  • 5+ years of hands-on experience in training ML models for production
  • Master’s degree in Machine Learning, Computer Science, Electrical/Computer Engineering, or related fields.
  • Proven record of influencing and partnering with PMs, Software Developers and Machine Learning engineers/scientists
  • PhD degree in Machine Learning, Computer Science, Electrical/Computer Engineering, or related fields, with good publication record
  • Experience in building and evaluating GenAI-based products or features
  • Proficiency of using analytical tools (e.g.: Jupyter Notebook) for data analysis and visualization
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 $181,100 and $318,400, 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.

Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote 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.

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