Apple Maps enables millions of delightful user experiences every day. Our mission is clear - to build the freshest, most accurate maps, powering features that to let users explore and navigate the world. We are seeking a senior architect who is passionate about leveraging cutting-edge machine learning techniques to develop our next-gen architecture focused on creating, updating and enriching business and places data while optimizing latency and cost. If you are driven by applying multi-modal ML techniques to global scale data challenges, thrive on building sophisticated data pipelines, and launching features that impacts millions of users daily, we may have a role for you. Passionate about creating robust systems using Gen AI, LLMs and other emerging technologies at scale? This could be the perfect opportunity for you!
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Description
Businesses and places in the real world are in constant flux. Capturing this change accurately and quickly is both highly challenging and rewarding. Keeping the dynamic dataset of places up-to-date demands significant investments in Machine Learning. From Natural Language Processing to Computer Vision to Generative AI, the Maps Places Data Pipeline leverages cutting-edge ML techniques to process, interpret, and contextualize information from unstructured Internet documents, structured data providers, street and aerial imagery, probe data, and many other sources. ML models synthesize a rich and up-to-date digital representation of the world. As a senior architect on the team, you will be responsible for design, technology selection and implementation of systems built to handle relentless streams of change signals associated with our global Places database. You will drive the platform and architectural choices to enable complex, agentic workflows for multi-modal information extraction, geospatial processing and data updates. You will own design trade-offs between throughput, latency and cost of keeping Places data as accurate as possible. You will collaborate with world-class cross-functional teams, including engineers, data analysts, labelers, and validators, to develop innovative solutions. Your solutions will enable content and domain experts to experiment and iterate rapidly with data at scale without being exposed to the underlying compute complexity. By enabling our teams to build the freshest and most accurate data, your contributions will power seamless and delightful user experiences. Senior engineers at Apple balance both technical execution and the long-term vision for their team. They collaborate effectively with partner and product teams to refine requirements, shape roadmaps and release delightful experiences that uphold Apple's core values. As a technical leader, you will provide also provide technical guidance and mentorship to team members. Strong interpersonal skills are essential for communicating technical complexities clearly to engineering partners, product management teams, and executives across Apple.
Minimum Qualifications
- 10+ years of experience in developing and deploying large scale, ML-centric systems and data pipelines on complex data domains in production settings.
- 5+ years of hands-on-experience with using ML models in production systems to ship customer-facing features. Experience in one or more of the following domains: Algorithms, Architecture, Artificial Intelligence, Data Mining, Deep Neural Networks, Distributed Systems, Information Retrieval, Machine Learning, Natural Language Processing, and Computer Vision.
- Strong foundational understanding of principles of distributed systems for large scale data processing; hands-on-experience with cloud platforms like AWS, GCP or Azure.
- Deep mastery of developing & supervising production code in Scala, Java or C++ using ML toolkits like PyTorch, TensorFlow, Scikit-learn.
- Familiarity with big data technologies like Spark, Solr/Lucene, Cassandra
- Proven ability to translate requirements from design to implementation, both independently and within larger teams.
- Demonstrated track record of making complex technical decisions and driving outcomes.
- Master's degree or equivalent experience in AI, Machine Learning, Mathematics, Computer Science, or a related field.
Preferred Qualifications
- PhD or Master's degree in AI, Machine Learning, Computer Science, Mathematics, or a related field.
- Experience in evaluating and deploying multiple search features, including large-scale machine learning models, deep learning, and natural language processing solutions.
- Experience with geospatial data is a plus.
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 $207,800 and $378,700, 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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