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data engineer, part dataops Jobs in Cupertino

data engineer, part dataops

data engineer part dataops

Apple

The people here at Apple don&rsquo;t just create products - they create the kind of wonder that&rsquo;s revolutionized entire industries. It&rsquo;s the diversity of those people and their ideas that inspires the innovation that runs through everything we do, from amazing technology to industry-leading environmental efforts. 
 
Apple is seeking an experienced, detail-minded data engineering team lead to join our Finance Process, Analytics, Reporting &amp; Technology (PART) Data Operations team. You will lead a team of data engineers delivering trustworthy, high-quality data to our Retail Finance analysts. If you are someone who looks forward to solving complex business problems, developing engineering talent, and building reliable data foundations, please reach out to us. 
 
Description 
 
You will lead a team of data engineers to architect, develop, and test large scale and efficient solutions that provide Apple leadership with the accurate data required to rapidly understand and adapt to changing business conditions. 
 
We are a growing team with plenty of interesting technical and business challenges to solve. We seek a self-starter who is willing to learn fast, adapt well to changing requirements, develop others, and work with cross functional teams.&quot;,&quot;responsibilities&quot;:&quot;Lead, mentor, and develop a team of data engineers, setting technical standards and fostering a culture of engineering excellence 
 
Design and implement scalable, efficient, and high-quality methods of consuming data from a diverse set of sources with variable quality and predictability 
 
Establish and maintain data quality frameworks, including automated validation, monitoring, and alerting 
 
Create data products, enabling self-service and predictability by any consumer 
 
Build libraries and frameworks that drive leverage and productivity for the entire team 
 
Optimize and maintain solutions, driving improvements in efficiency, data quality, and operational excellence 
 
Manage team workload and priorities, balancing competing demands while maintaining quality 
 
Preferred Qualifications 
 
2+ years leading or mentoring other engineers 
 
Expertise in languages like Python and technologies like Airflow, Spark, Trino, Kafka, Docker, Iceberg, Databricks 
 
Hands-on experience with database design and architecture in cloud data warehouses and lakehouse environments 
 
Ability to analyze complex datasets and design solutions with optimum quality and efficiency 
 
Appreciation for data quality and validation in every pipeline 
 
Familiarity with SDLC best practices, version control, CI/CD 
 
Strong communication skills with the ability to translate between technical and business contexts 
 
Experience with cloud services such as AWS, GCP, or Azure for data infrastructure and storage 
 
Experience with streaming interfaces and pipelines 
 
Finance and accounting process experience 
 
Minimum Qualifications 
 
6+ years software engineering, including strong SQL and data focus 
 
BS in Engineering / Computer Science 
 
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 . 
 
Pay &amp; 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 $146,300 and $244,100, 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.

Data Engineer, PART DataOps

Services Finance Data Science and Engineering team is looking for a passionate and highly motivated Data Engineer to drive our financial data platform forward. You will provide a key function in shaping the success of Apple&rsquo;s current and future products. As members of the Services Finance Data Science and Engineering team, we work with various business and engineering teams to understand current and future business initiatives. We need to be persistent and flexible in extracting data from various sources, cleaning and curating this data, and then clearly and concisely communicating insights. 
 
Description 
 
The individual in this role will collaborate with data scientists, business analysts and subject matter experts (SME) to acquire, and transform raw data and develop sophisticated data products. This includes developing and maintaining data pipelines, extracting from different sources (databases, APIs, etc.), and transforming raw data into normalized tables after running data quality checks. A successful data engineer is skilled in taking a business problem and translating it into a data solution in close collaboration with data scientists, business analysts, and SMEs.&quot;,&quot;responsibilities&quot;:&quot;Building and maintaining pipelines to extract data from various external sources (e.g. databases, APIs, etc..) and move data to internal destinations (e.g. Snowflake, Cloud Storage, etc..) 
 
Maintain data dictionary, lineage and documentation 
 
Enhance existing Pipeline monitoring and develop functionality for data observability 
 
Enable Analysts and Tableau developers by curating datasets which are easily accessible 
 
Work with SME to understand the data requirements and to translate business problems into data solutions and products 
 
Monitor the health status of the tables and data pipelines and develop an alerting system for failures and problems 
 
Conduct POCs and test new methods and technologies based on the team needs 
 
Preferred Qualifications 
 
Experience with scheduling systems and CI/CD tools such as Airflow, Jenkins, etc. 
 
Understanding of dimensional modeling, data warehousing concepts, medallion and data lakehouse architectures 
 
Hands-on experience with building ETL process and writing unit tests using DBT or similar tools 
 
Minimum Qualifications 
 
Minimum of 5 years of working experience as a data engineer building end-to-end data pipelines 
 
Advanced SQL skills for complex transformations, optimization, and troubleshooting 
 
A Bachelor&rsquo;s degree in Statistics, Computer Science, Computer Engineering, or equivalent practical experience 
 
Python proficiency, comfortable writing clean, maintainable Python for data pipelines and automation 
 
Hands-on experience working with relational database management system such as Snowflake, PostgreSQL or similar cloud data warehouses 
 
Ability to work both independently and within a team environment 
 
Strong written and verbal communication skills, capable of explaining technical results to a non-technical audience 
 
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 . 
 
Pay &amp; 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 $118,500 and $197,500, 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.

Services Finance Data Engineer

Apple&rsquo;s Health Sensing team is seeking a versatile Machine Learning Engineer to develop next-generation health algorithms that deliver meaningful insights to users by combining classical ML, signal processing, and emerging generative AI techniques. Our team has delivered impactful features including heart rate notifications, ECG, blood oxygen, sleep apnea notifications, and overnight vitals to millions of Apple Watch users. 
 
Description 
 
This role is ideal for an engineer who enjoys moving quickly from idea to prototype to product, creatively overcoming data limitations, and applying new tools to multi-modal sensor fusion problems in health and wellness. You will work across the full algorithm lifecycle including data strategy, modeling, evaluation, optimization, and deployment.&quot;,&quot;responsibilities&quot;:&quot;Develop and validate ML and GenAI-driven algorithms for health sensing applications from concept through productization 
 
Prototype and compare multiple approaches using real and synthetic data to accelerate algorithm development 
 
Design experiments and evaluation methodologies to quantify performance and guide algorithm improvements 
 
Optimize algorithms for robustness, efficiency, and on-device deployment constraints 
 
Work cross-functionally with user studies, hardware, software, and product teams to bring algorithms into product 
 
Analyze failure modes, quantify tradeoffs, and drive data-driven algorithm improvements 
 
Preferred Qualifications 
 
Experience developing algorithms for physiological sensing using multi-modal data 
 
Familiarity with on-device ML frameworks or resource-constrained optimization 
 
Experience working with incomplete, noisy, or limited datasets 
 
Background in experimental design and statistical validation 
 
Experience with distributed or cloud-based ML workflows 
 
Experience accelerating development through simulation, synthetic data, or creative data augmentation approaches 
 
Self-driven, curious engineer comfortable taking ambiguous sensing problems from concept to working solutions 
 
Minimum Qualifications 
 
Bachelors degree in Computer Science, Electrical Engineering, Biomedical Engineering, Statistics, Applied Mathematics, or related field, or equivalent industry experience. 
 
Strong foundation in machine learning, statistics, signal processing, or applied mathematics for real-world sensing problems 
 
Experience applying modern AI techniques, including generative AI and agentic AI, to accelerate algorithm development, data generation, and performance evaluation 
 
Proficiency in Python for algorithm development and optimization 
 
Demonstrated ability to rapidly prototype, evaluate multiple approaches, and iterate based on experimental results 
 
Experience owning algorithm development from early exploration through validation and integration 
 
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 . 
 
Pay &amp; 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 $139,500 and $258,100, 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.

Machine Learning Engineer

Are you excited to tackle some of the most ambitious technical challenges in Apple Intelligence? Be involved in collaborating closely with our machine learning researchers, engineers, and data scientists? Together, you will orchestrate groundbreaking research initiatives and develop transformative products designed to build a significant impact for billions of users worldwide! 
 
As part of Apple's AI and Machine Learning org, we encourage and create groundbreaking technology for large-scale ML systems, computer vision, natural language processing, and multi-modal understanding and generation. The Data and Machine Learning Innovation (DMLI) team is looking for Machine Learning Engineer to explore new methods, challenge existing metrics or protocols, and develop new insightful practices that will change how we understand data and overcome real-world ML challenges. 
 
Description 
 
As a Machine Learning (ML) Engineer, you will be entrusted with the critical role of innovating and applying state of the art research in ML to tackle complex data problems. The solutions you develop will significantly impact Apple Intelligence, future Apple products and the broader ML development ecosystem. 
 
You will work with a multidisciplinary team to actively participate in Apple Intelligence&rsquo;s data-model co-design and co-develop practice. Your responsibilities will extend to the design and development of a comprehensive data generation and curation framework for Apple Intelligence foundation models at Apple. You will also be responsible to build robust model evaluation pipelines, integral to the continuous improvement and assessment of Apple Intelligence foundation models. 
 
Furthermore, you will have the opportunity to showcase your groundbreaking research work by publishing and presenting at premier academic venues. 
 
Your work may span a variety of directions, including but not limited to: 
 
Develop and implement techniques for creating high-quality synthetic datasets across a variety of domains, including vision, text, and audio data. 
 
Innovate and experiment with new approaches for synthetic data generation to improve the diversity, realism, and representativeness of datasets. 
 
Collaborate with multi-functional teams to understand data requirements and ensure that synthetic datasets are optimized for training foundation models. 
 
Crafting and implementing semi-supervised, self-supervised representation learning techniques for growing the power of both limited labeled data and large-scale unlabeled data. 
 
Develop pipelines and tools to automate synthetic data generation for large-scale AI experiments. 
 
Stay updated with the latest research and industry trends in synthetic data generation, foundational model training, and large-scale data engineering. 
 
Preferred Qualifications 
 
3+ years of experience with developing and evaluating ML applications, and demonstrated experience in understanding and improving data quality. 
 
Strong publication record in relevant conferences (e.g. CVPR, ICCV, ECCV, NeurIPS, ICML, ICLR, , etc) 
 
Strong problem-solving and communication skills. 
 
Ph.D/MS degree in Machine Learning, Natural Language Processing, Computer Vision, Data Science, Statistics or related areas 
 
Minimum Qualifications 
 
Demonstrated expertise in computer vision, natural language processing, and machine learning with a passion for data-centric machine learning. 
 
Deep understanding in multi-modal foundation models. 
 
Staying on top of emerging trends in generative AI and multi-modal LLM. 
 
Strong programming skills and hands-on experience using the following languages or deep learning frameworks: Python, PyTorch, or Jax. 
 
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 . 
 
Pay &amp; 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 $147,400 and $272,100, 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.

AIML - Machine Learning Engineer, Data and ML Innovation

The Apple Ray team is seeking a Senior / Staff Software Engineer with strong distributed systems expertise and a solid background in machine learning. In this hybrid role, you will design and build core components of Apple&rsquo;s unified data+ML platform powered by open-source Ray, while also partnering with ML teams to ensure the platform meets the needs of large-scale training and inference workloads. 
 
You will contribute to the distributed runtime, orchestration layer, and system APIs that power Apple&rsquo;s intelligent features across products and services. This role is ideal for a software engineer who enjoys low-level systems work but is also fluent in ML workflows and models at scale. 
 
Description 
 
Apple Ray integrates deeply with Apple&rsquo;s data and ML ecosystem to provide a unified platform for building, orchestrating, and scaling complex ML and data pipelines. As a Software Engineer with ML background, you will design distributed systems that support large-scale model training, tuning, and inference across heterogeneous compute environments-from bare-metal GPU clusters to cloud-native infrastructure. 
 
You will build features that enhance developer productivity for ML engineers, improve resource efficiency, and advance the performance and reliability of Apple&rsquo;s ML workloads. You&rsquo;ll collaborate closely with ML practitioners to translate model and pipeline needs into robust platform capabilities, while also improving the underlying distributed runtime and control plane. 
 
This role requires strong engineering fundamentals, hands-on experience with ML systems, and a passion for building scalable infrastructure.&quot;,&quot;responsibilities&quot;:&quot;Build scalable distributed systems and platform components using Ray that power Apple&rsquo;s data+ML workflows. 
 
Develop APIs, libraries, and services that improve the efficiency and usability of large-scale ML training and inference pipelines. 
 
Optimize performance and resource utilization across GPU/CPU clusters for ML workloads running at Apple scale. 
 
Collaborate with ML teams to understand model and pipeline needs and translate them into robust platform features. 
 
Design fault-tolerant orchestration mechanisms, autoscaling strategies, and runtime improvements for distributed ML jobs. 
 
Diagnose complex issues across distributed systems and ML pipelines to ensure reliability and availability. 
 
Improve observability, monitoring, and debugging capabilities targeted at ML-centric distributed workloads. 
 
Contribute to architectural decisions and, where appropriate, upstream enhancements to Ray and related tools. 
 
Preferred Qualifications 
 
Experience with distributed training frameworks (DeepSpeed, Horovod, FSDP, ZeRO). 
 
Background in optimizing GPU workloads or performance benchmarking. 
 
Experience with model orchestration systems or ML platforms. 
 
Contributions to open-source ML or distributed systems projects. 
 
Familiarity with large-scale data systems such as Spark, Flink, or similar. 
 
Minimum Qualifications 
 
6+ years building distributed systems, high-scale backend services, or compute runtimes. 
 
Solid background in ML workflows, model training, model serving, or data pipeline development. 
 
Proficiency in Python, plus strong experience in a systems-level language (C++, Rust, Go, or Java). 
 
Experience with ML frameworks such as PyTorch or TensorFlow and familiarity with GPU-based training. 
 
Understanding of parallelism strategies, model scaling, or distributed training concepts. 
 
Experience with cluster orchestration (Kubernetes, EKS, GKE) or large-scale compute systems. 
 
Strong debugging skills across distributed and ML-centric runtime environments. 
 
Ability to work cross-functionally with ML engineers, data engineers, and infrastructure teams. 
 
B.S., M.S., or Ph.D. in Computer Science, Machine Learning, or related technical fields - or comparable software engineering experience. 
 
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 . 
 
Pay &amp; 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 $147,400 and $272,100, 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.

Senior ML Engineer, Apple Ray, Apple Data Platform

Would you like to be a part of Apple&rsquo;s AI and Machine Learning org, where we encourage and create groundbreaking technology for multi-modal models with strong agent and reasoning capabilities? The Data and Machine Learning Innovation (DMLI) team is seeking a passionate Machine Learning Engineer to explore new methods, challenge existing metrics and protocols, and develop new insightful practices for real-world ML challenges. As a team member, you will work on some of the most ambitious technical challenges in the field. Your role will involve collaborating closely with our team of machine learning researchers, engineers, and data scientists. Together, you will spearhead groundbreaking research initiatives and develop transformative products designed to build for billions of users worldwide. 
 
Description 
 
As a Machine Learning (ML) Engineer, you will be entrusted with the critical role of innovating and applying innovative research in foundation models to with a particular focus on audio data. This includes working across the full ML pipeline-from pre-training on large-scale unlabeled audio corpora to post-training evaluation and fine-tuning with task-specific datasets. The solutions you develop will have a significant impact on future Apple software and hardware products, as well as the broader ML ecosystem. 
 
Your responsibilities will extend to designing and developing a comprehensive multi-modal data generation and curation framework for foundation models at Apple. You will also contribute to building robust model evaluation pipelines that support continuous improvement and performance assessment. In addition, the role involves analyzing multi-modal data to better understand its influence on model behavior and outcomes. Furthermore, you will have the opportunity to showcase your groundbreaking research work by publishing and presenting at premier academic venues. 
 
YOUR WORK MAY SPAN VARIOUS APPLICATIONS, INCLUDING: 
 
Designing self-supervised and semi-supervised representation learning pipelines, and fine-tuning strategies for tasks like speech recognition and speaker identification. 
 
Applying data selection techniques such as novelty detection and active learning across multi modalities to improve data efficiency and reduce distributional gaps. 
 
Modeling data distributions using ML/statistical methods to uncover patterns, reduce redundancy, and handle out-of-distribution challenges. 
 
Rapidly learning new methods and domains as needed, and guiding product teams in selecting effective ML solutions. 
 
Preferred Qualifications 
 
Deep understanding of multi-modal foundation models. 
 
Staying up-to-date with emerging trends in generative AI and multi-modal LLMs. 
 
The ability to formulate machine learning problems, design, experiment, implement, and communicate solutions effectively with multi-functional teams. 
 
Demonstrated publication records in relevant conferences (e.g., CVPR, ICCV, ECCV, NeurIPS, ICML, ICLR, etc.). 
 
Track records of adopting ML to solve cross-disciplinary problems. 
 
Minimum Qualifications 
 
Deep technical skills in one or more machine learning areas, such as computer vision, audio, combinatorial optimization, causality analysis, natural language processing, and deep learning. 
 
Strong software development skills with proficiency in Python; hands-on experience working with deep learning toolkits like PyTorch, TensorFlow, or JAX (one of). 
 
5+ years of experience developing and evaluating ML applications, demonstrating a passion for understanding and improving model/data quality.&lsquo; 
 
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 . 
 
Pay &amp; 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 $147,400 and $272,100, 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.

AIML - Sr Machine Learning Engineer - Data and ML Innovation

The Maps Data Platform Workflows Team oversees the processing and management of data and workflows at the core of Apple Maps. We build and maintain the systems that enable processing and workflow management of petabytes of map data that powers the Apple Maps experience used by millions of people every day! 
 
As a Maps Data Platform engineer, youʼll design and help implement systems which empower teams across engineering and operations to build our future Apple Maps experiences! 
 
Description 
 
The Maps Data Platform Workflows Team builds and maintains the foundation that powers Apple Maps. We are responsible for providing scalable and extensible workflows that handles petabytes of map data, enabling various aspects of Map building including but not limited to data ingest, map updates, review process, and traceability. 
 
As a full-stack engineer on the team, you will primarily be responsible to build user experiences that powers various workflows involved in Map building life cycle. This position is ideal for innovative engineers who are passionate and excited to work in complex, fast-paced and ambiguous environments to deliver tangible results keeping in mind our end users and their experiences.&quot;,&quot;responsibilities&quot;:&quot;Build user experiences that powers various workflows involved in Map building life cycle. 
 
Implement foundational platform components to support Generative-AI based multi agent systems. 
 
Work closely with multi functional teams to enhance and improve our workflow solutions. 
 
Design and implement scalable and extensible platform components to support the user experiences across a dynamic range of use cases. 
 
Implement foundational platform components to to support Generative-AI based multi agent systems. 
 
Partner with a wide array of cross functional partner teams and stakeholders to understand the requirements to help build the best-in-class user experiences. 
 
Drive end-to-end delivery of the software projects and enable platform users across the Maps organization. 
 
Support and improve new and existing user experiences that power Apple Maps. 
 
Preferred Qualifications 
 
Experience with platform based approach to building user experiences with integration with REST and/or GraphQL APIs to enable scalability and reusability. 
 
Experience with Geospatial applications or mapping libraries (Mapbox, Leaflet or similar) 
 
Understanding of authentication and authorization mechanisms, including JWT and OAuth. 
 
Proven success applying Generative AI to production systems beyond prompt engineering. 
 
Minimum Qualifications 
 
Bachelor&rsquo;s degree and 4+ years of experience building and maintaining production systems. 
 
Strong hands-on experience with React, including hooks, context, and performance optimization techniques. Proficiency in TypeScript for building scalable and maintainable frontend applications. 
 
Experience with modern state management solutions such as Redux Toolkit, React Query, or Apollo. 
 
Familiarity with data visualization and charting libraries such as Highcharts, Recharts, Chart.js, or D3. 
 
Solid understanding of component-based architecture and reusable UI patterns. 
 
Experience in building scalable and low latency JVM-based web services using Scala or Java. 
 
Strong understanding of distributed data storage systems (both databases and indexes). 
 
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 . 
 
Pay &amp; 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 $147,400 and $272,100, 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.

Full Stack Engineer - Maps Data Platform Workflow Team

Explore 107+ Data engineer part dataops in Cupertino this April. Find roles across top companies and apply now to boost your career.