Machine Learning Engineer, Maps

Apple; Cupertino (CA); On-site; USD 143,000 - 265,000; Full time

Job summary

A leading company is seeking a Machine Learning Engineer for its Arrival Experience team in Cupertino. This role involves designing and deploying advanced machine learning models to enhance navigation accuracy for Apple Maps users. The ideal candidate will have a strong background in computer vision and generative AI, working on complex real-world problems that impact millions of users.

Benefits

Comprehensive medical and dental coverage

Retirement benefits

Discounted products and free services

Educational reimbursement

Discretionary bonuses or commission payments

Qualifications

• 2+ years of experience in machine learning, particularly in computer vision.
• Experience with transformer-based architectures.
• Strong collaboration and communication skills.

Responsibilities

• Build and deploy ML models integrating imagery and spatial context.
• Design generative AI-based systems to enhance user experiences.
• Evaluate models using automated metrics and real-world feedback.

Skills

Machine Learning

Computer Vision

Generative AI

Python

Problem Solving

Education

MS or PhD in Computer Science

Tools

PyTorch

Job description

Machine Learning Engineer, Maps

**Cupertino, California, United States**

**Machine Learning and AI**

**Summary**

Posted: **May 17, 2025**

Weekly Hours: **40**

Role Number: **200602144**

The Arrival Experience is a defining moment in how users interact with the real world through Maps. As we make navigation more intelligent and context-aware, this experience becomes central to delivering precision and confidence; helping users reach the exact place they intend to go. Whether it’s a storefront, parking entrance, or doorstep, we are building the intelligence that powers this crucial interaction for hundreds of millions of Apple Maps users.

As a Machine Learning Engineer on the Arrival Experience team, you’ll design and deploy models that blend satellite and aerial imagery, behavioral signals, and map metadata to deliver precise, intuitive destination guidance. You’ll also develop generative AI-based multi-agent systems that can dynamically reason, evaluate, and improve guidance quality at scale.

This role offers the opportunity to solve highly complex, real-world problems at the intersection of geospatial intelligence, computer vision, and generative AI.

At Apple, we build products that enrich people’s lives, and we believe even the smallest moments, like arriving confidently at the right place, are part of that promise. As part of the Arrival Experience team, your work will help turn complex geospatial systems into intuitive everyday magic for hundreds of millions of users.

**Description**

Are you passionate about building intelligent systems that seamlessly integrate various data modalities? As a Machine Learning Engineer on our Arrival Experience team, you will:

- Build and deploy ML models that integrate imagery, spatial context, and user behavior to enhance arrival accuracy

- Design and implement generative AI-based multi-agent systems that evaluate and improve arrival experiences

- Work closely with product and engineering teams to bring model intelligence into user-facing features

- Evaluate models using both automated metrics and real-world feedback, continuously iterating for quality

- Stay informed on advances in computer vision, generative AI, and applied machine learning to explore new approaches and keep the system adaptive and future-ready

**Minimum Qualifications**

+ MS or PhD in Computer Science, Machine Learning, or a related field.

+ 2+ years of hands-on experience in machine learning, particularly in computer vision or multimodal model development

+ Experience building and deploying transformer-based architectures, including Vision Transformers (ViT), or multimodal vision-language models such as CLIP

+ Familiarity with multi-agent system design and orchestration frameworks, including the use of Model Context Protocol (MCP), A2A (agent-to-agent) communication systems, or LangGraph for generative agent workflows

+ Proficiency in Python with deep expertise in PyTorch for model development and deployment

+ Experience working with large-scale datasets and building scalable training or inference pipelines

+ A self-starter with a go-getter attitude, able to work around data limitations or organizational constraints and continue making progress

+ Excellent problem-solving skills with the ability to approach ambiguous problems creatively

+ Strong collaboration and communication skills with a track record of working effectively across teams

+ Commitment to fostering an open, inclusive, and team-oriented work environment

**Preferred Qualifications**

+ Demonstrated success applying generative AI to production systems beyond prompt engineering

+ Familiarity with extracting and refining polygonal features from imagery, including post-processing techniques such as the Marching Squares algorithm or similar contour extraction methods

+ Experience working with geospatial data formats such as GeoTIFF, raster maps, shapefiles, or GeoJSON

**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 $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. (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) .

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) .

Apple will not discriminate or retaliate against applicants who inquire about, disclose, or discuss their compensation.

Apple participates in the E-Verify program in certain locations as required by law.Learn more about the E-Verify program (https://www.apple.com/jobs/pdf/EverifyPosterEnglish.pdf) .

Apple is committed to working with and providing reasonable accommodation to applicants with physical and mental disabilities. Reasonable Accommodation and Drug Free Workplace policy Learn more .

Apple is a drug-free workplace. Reasonable Accommodation and Drug Free Workplace policy Learn more .

Apple will consider for employment all qualified applicants with criminal histories in a manner consistent with applicable law. If you’re applying for a position in San Francisco, review the San Francisco Fair Chance Ordinance guidelines applicable in your area.

It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.