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Machine Learning Engineer - Maps Search Job Opening In Cupertino – Now Hiring Apple

Machine Learning Engineer Maps Search

    United States Jobs Expertini Expertini › United States › Jobs › Cupertino › Other General › Machine Learning Engineer Maps Search

Job description

**Weekly Hours:** 40
**Role Number:** 200623892-0836

**Summary**
Apple Maps and the thousands of applications it empowers are being used by millions every single day! As a fundamental tool for human activity, Maps technology is evolving and new techniques are emerging.
We are looking for a Machine Learning Engineer to join and help play a big part in the next revolution of Maps; to enable users to find more things in innovative ways.

On our team, you will have plenty of opportunities to build groundbreaking technologies using ML and GenAI at scale to improve the search quality for Apple Maps.

**Description**
The goal of Maps Search team is to take Apple’s Maps to the next level of intelligence and accuracy using machine learning and artificial intelligence techniques.

Engineers and scientists on our team work on a wide spectrum of approaches to improve search experiences on Apple Maps.
This position involves a wide variety of skills and innovation; It is a unique opportunity that sits at the intersection of science and engineering.

Ultimately, your work would have a huge impact on millions of users across the globe, so join us and help us in building a world class search team!

**Minimum Qualifications**

+ MS in computer science or equivalent field with 7+ years of industry experience
+ Proven record in delivering end-user facing ML driven products
+ Strong programming experience in one or more of the following: Java, C++, Python
+ Knowledge and experience with one of Tensorflow/Pytorch/Jax frameworks
+ Excellent interpersonal and communication skills - working independently and/or in small teams
+ Attention to detail, data accuracy and quality of output

**Preferred Qualifications**

+ Ph.D in Computer Science or equivalent field with 7+ years of industry experience
+ Expertise and experience in various facets of machine learning and natural language processing, such as classification, feature engineering, information extraction, clustering, semi-supervised learning, topic modeling and ranking
+ Practical understanding of the mathematics behind modern machine learning, linear algebra and statistics
+ Good knowledge of big data processing, prior experience with Hadoop, Spark, and Hive is highly desired
+ Knowledge and prior experience with some deep learning and GenAI frameworks and LLMs
+ Prior experience in consumer facing product development and delivery
+ Prior experience as a team lead

**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 $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.

(https://www.apple.com/careers/us/benefits.html)

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 (https://www.eeoc.gov/sites/default/files/2023-06/22-088_EEOC_KnowYourRights6.12ScreenRdr.pdf) .


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Unlock Your Machine Learning Potential: Insight & Career Growth Guide


Real-time Machine Learning Jobs Trends (Graphical Representation)

Explore profound insights with Expertini's real-time, in-depth analysis, showcased through the graph here. Uncover the dynamic job market trends for Machine Learning in Cupertino, United States, highlighting market share and opportunities for professionals in Machine Learning roles.

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Are You Looking for Machine Learning Engineer Maps Search Job?

Great news! is currently hiring and seeking a Machine Learning Engineer Maps Search to join their team. Feel free to download the job details.

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2. Loyalty

3. Impartiapty

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6. Respect for human rights

7. Obeying United States laws and regulations

What Is the Average Salary Range for Machine Learning Engineer Maps Search Positions?

The average salary range for a varies, but the pay scale is rated "Standard" in Cupertino. Salary levels may vary depending on your industry, experience, and skills. It's essential to research and negotiate effectively. We advise reading the full job specification before proceeding with the application to understand the salary package.

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Key qualifications for Machine Learning Engineer Maps Search typically include Other General and a list of qualifications and expertise as mentioned in the job specification. The generic skills are mostly outlined by the . Be sure to check the specific job listing for detailed requirements and qualifications.

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Interview Tips for Machine Learning Engineer Maps Search Job Success

Apple interview tips for Machine Learning Engineer Maps Search

Here are some tips to help you prepare for and ace your Machine Learning Engineer Maps Search job interview:

Before the Interview:

Research: Learn about the Apple's mission, values, products, and the specific job requirements and get further information about

Other Openings

Practice: Prepare answers to common interview questions and rehearse using the STAR method (Situation, Task, Action, Result) to showcase your skills and experiences.

Dress Professionally: Choose attire appropriate for the company culture.

Prepare Questions: Show your interest by having thoughtful questions for the interviewer.

Plan Your Commute: Allow ample time to arrive on time and avoid feeling rushed.

During the Interview:

Be Punctual: Arrive on time to demonstrate professionalism and respect.

Make a Great First Impression: Greet the interviewer with a handshake, smile, and eye contact.

Confidence and Enthusiasm: Project a positive attitude and show your genuine interest in the opportunity.

Answer Thoughtfully: Listen carefully, take a moment to formulate clear and concise responses. Highlight relevant skills and experiences using the STAR method.

Ask Prepared Questions: Demonstrate curiosity and engagement with the role and company.

Follow Up: Send a thank-you email to the interviewer within 24 hours.

Additional Tips:

Be Yourself: Let your personality shine through while maintaining professionalism.

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Turn Off Phone: Avoid distractions during the interview.

Final Thought:

To prepare for your Machine Learning Engineer Maps Search interview at Apple, research the company, understand the job requirements, and practice common interview questions.

Highlight your leadership skills, achievements, and strategic thinking abilities. Be prepared to discuss your experience with HR, including your approach to meeting targets as a team player. Additionally, review the Apple's products or services and be prepared to discuss how you can contribute to their success.

By following these tips, you can increase your chances of making a positive impression and landing the job!

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