Cupertino, CA

Developer Jobs in Cupertino, CA

38 jobs found

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Today

Senior Data Engineer

Apple Cupertino, CA

Cupertino, CA

Today

$185k - $325k/yr Full time Senior Apache Spark Big Data

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Job Description

Apple Services Engineering’s Device Compute Analytics team is hiring a Senior Data Engineer to build and operate a data lakehouse that converts device and compute events into accurate, timely, fast-to-query tables.

Responsibilities

Own a data lakehouse that transforms raw device and compute events into reliable, fast-to-query tables
Build and run Apache Spark pipelines
Design analytics tables queried via Trino for downstream dashboards
Implement data quality checks to keep data accurate and timely
Over time, take over event ingestion from Kafka
Create trustworthy datasets from device lifecycle, job and session activity, provisioning, and failures events landing in Iceberg
Collaborate with a data analyst and a full-stack engineer responsible for dashboards, plus application engineers and cross-functional teams across Apple

Requirements

Bachelor’s degree in Computer Science, Engineering, or a related field
7+ years of professional data engineering experience building production data pipelines at scale, including diagnosing and improving performance of data jobs and queries, or equivalent advanced degree plus experience
Production experience with Apache Spark, including batch and Structured Streaming
Strong data modeling skills, including designing analytics schemas on Apache Iceberg or comparable lakehouse table formats
Proficiency in Java or Scala and strong SQL
Experience building data quality checks and monitoring for production pipelines, including freshness and completeness alerting and reconciliation between source and derived data
Productive use of AI coding tools in real delivery, with discipline to validate generated code and queries
Excellent communication and critical thinking in a team environment

Technologies

Apache Spark
Structured Streaming
Apache Iceberg
Trino
Kafka
SQL
Java
Scala

Preferred Qualifications

Production experience with Apache Kafka as a streaming source
Production experience with Apache Flink, including the Iceberg sink, exactly-once delivery, and stateful jobs on Kubernetes
Experience with data contracts and schema management as code (for example schema registries or dbt model contracts)
Experience tuning tables and queries for a distributed SQL engine such as Trino
Experience with workflow orchestration and Python automation
Experience building dashboards or data applications for users with attention to visual design
Experience owning the design of a data platform or pipeline, not just implementing it
Experience mentoring engineers and leading cost or reliability improvements

Benefits

Comprehensive medical and dental coverage
Retirement benefits
Range of discounted products and free services
Reimbursement for certain educational expenses, including tuition
Discretionary bonuses or commission payments, as well as relocation (if eligible)
Opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs
Eligibility for discretionary restricted stock unit awards
Ability to purchase Apple stock at a discount if voluntarily participating in Apple’s Employee Stock Purchase Plan

Location: Cupertino, CA (onsite)

Salary: USD 184,700 - 324,800 per year

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Today

Data Engineer

Apple Cupertino, CA

Cupertino, CA

Today

$129k - $195k/yr Full time Artificial Intelligence Big Data Bigdata

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Job Description

Build privacy-focused data engineering and machine learning systems for advertising at Apple Ads within the Data Org.

Responsibilities

Engineer secure, scalable data and machine learning systems for real-time, near-real-time, and batch processing using Spark, Kafka, Iceberg, and related technologies
Own end-to-end delivery of core components, from pipeline architecture to ML model development, training, and deployment
Design and support privacy-preserving, mission-critical data and ML infrastructure
Improve reliability, performance, and efficiency across systems, including schema changes and backfills
Build and maintain experimentation and testing infrastructure to validate changes (including A/B testing)
Apply strong understanding of the intersection between business, analytics, and engineering to deliver reusable, efficient solutions
Use LLMs and AI coding agents (e.g., Claude, Gemini) daily for implementation, testing, and debugging while validating results for correctness, privacy, and cost
Collaborate with engineers and product managers through code and design reviews; mentor others as seniority increases
Participate in on-call, monitoring, and continuous reliability and efficiency improvements; more senior engineers lead incident response and root-cause analysis
Work in an Agile, sprint-based environment with emphasis on reliability, resiliency, extensibility, scalability, and productivity

Requirements

1+ years of industry experience building scalable data pipelines and machine learning systems, or other distributed software at scale
Strong computer science and software engineering fundamentals
Proficiency in modern programming languages such as Rust, Python, Java, or Scala
Experience with distributed systems and data processing technologies, such as Spark, Kafka, Flink
Experience building and scaling systems on premise and in the cloud
Solid understanding of data structures, algorithms, and system design
Ability to communicate effectively with cross-functional teams (technical and non-technical)
Hands-on experience using LLMs (e.g., Claude, Gemini) for daily engineering work including code generation, review, debugging, test writing, agentic loops, and evaluation systems
Excellent collaborative skills
BS/MS in Computer Science, Software Engineering, Distributed Systems, or a related field

Technologies

Spark
Kafka
Iceberg
Flink
Rust
Python
Java
Scala
LLMs
Claude
Gemini
A/B testing

Benefits

Comprehensive medical and dental coverage
Retirement benefits
Discounted products and free services
Reimbursement for certain educational expenses, including tuition
Opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs
Discretionary restricted stock unit awards
Purchase Apple stock at a discount with participation in Apple’s Employee Stock Purchase Plan
Discretionary bonuses or commission payments (as applicable)
Relocation (as applicable)

Preferred Qualifications

Experience with NoSQL datastores (e.g., Cassandra, Keyspaces, ElastiCache)
Experience with lakehouse and Iceberg table formats
Experience with anomaly detection
Experience with A/B experimentation frameworks
History of driving reliability, efficiency, or cost improvements, and mentoring other engineers
Comfort working in a rapidly changing environment with ambiguous requirements
Prior experience in the advertising industry (huge plus)

Location: Cupertino, CA (onsite)
Salary: USD 129,300 - 194,700 per year

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Today

Data Engineer - Capacity Planning

Apple Cupertino, CA

Cupertino, CA

Today

$129k - $225k/yr Full time Analytics Artificial Intelligence Capacity Planning

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Job Description

Apple’s Data Platform organization is building the data foundation that powers smarter infrastructure capacity planning across data and AI systems. In this onsite role in Cupertino, CA, you’ll help connect telemetry, workload demand, and financial signals so teams can understand utilization, forecast needs, and make higher-confidence planning and investment decisions.

What you’ll do

Combine infrastructure telemetry, workload demand, capacity commitments, and financial data into trusted datasets and data products.
Develop pipelines and analytical foundations to measure current utilization, forecast future requirements, surface capacity gaps, and improve infrastructure efficiency.
Partner with engineering and business teams to translate complex infrastructure data into actionable insights.
Collaborate closely with Engineering, CIBO, Finance, and Procurement to support better infrastructure planning and investment decisions.
Start with third-party cloud infrastructure, including GPUs, TPUs, compute, and storage, and expand over time to Apple-owned infrastructure.

What you bring

3+ years of experience in Data Engineering, Analytics Engineering, Infrastructure Analytics, or a related field.
Strong SQL skills and experience working with large datasets.
Experience with Python or another language used for data processing and automation.
Hands-on experience building data pipelines, data models, and analytical datasets.
Understanding of ETL/ELT patterns, including data quality and pipeline reliability.
Experience working with cloud billing and usage data from AWS, GCP, or Azure.
Proven ability to build data models that reconcile to a financial source of truth.
Understanding of AI and ML inference workloads and how model serving drives compute cost.
Strong analytical and problem-solving skills.
Ability to work effectively with both technical and non-technical partners.
Bachelor’s degree in a relevant quantitative field, or equivalent practical experience.

Technologies you’ll use

SQL, Python, ETL, ELT, AWS, GCP, Azure, AI, ML

Preferred background

Experience with infrastructure capacity planning, forecasting, or resource-management data.
Experience with GPU/TPU/CPU, storage, or cloud infrastructure.
Understanding of AI/ML infrastructure and accelerator utilization.
Experience with infrastructure cost, billing, or utilization datasets.
Exposure to tools such as Spark, Trino, Airflow, Kafka, or similar data-platform technologies.
Experience with Tableau or other visualization platforms.
Familiarity with infrastructure economics, cloud commitments, or capacity optimization.
Experience partnering with Engineering, Finance, or Procurement on infrastructure planning.

Compensation and benefits

Salary range: USD 129,300 - 225,300 per year.

Comprehensive medical and dental coverage
Retirement benefits
Discounted products and free services
Reimbursement for certain educational expenses, including tuition
Discretionary employee stock programs (discretionary restricted stock unit awards; ability to purchase Apple stock at a discount with voluntary participation in the Employee Stock Purchase Plan)
Discretionary bonuses or commission payments, and relocation (if eligible)

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Today

Finance Data Engineer

Apple Cupertino, CA

Cupertino, CA

Today

$149k - $249k/yr Full time Python Aws Data Engineer Cloud Data Engineering

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Job Description

The Finance Data Engineer role focuses on building data interfaces, pipelines, and code that support innovative data products for Apple Finance. This position emphasizes dependable, accurate, and consistent data solutions across enterprise data warehouse and lakehouse environments, with cross-functional collaboration to deliver data services.

Responsibilities

Partner with data scientists, machine learning engineers, software engineers, and business stakeholders to identify data needs and to capture, collect, load, and format data from external sources, internal systems, and the data warehouse.
Design, validate, deploy, monitor, document, and troubleshoot data pipelines and feature-ready datasets.
Coordinate with other engineers to establish and adopt best practices for translating finance use cases into data requirements, schemas, and retrieval patterns for RAG, agents, and other LLM workflows.
Evaluate emerging technologies and contribute to decisions that enable adoption of new tools and associated techniques.

Requirements

5+ years of relevant data engineering experience.
Undergraduate degree in Computer Science, MIS, Engineering, Mathematics, or another quantitative discipline, with five or more years of experience.

Technologies

Python, shell, SQL
Snowflake, S3, AWS
Kubernetes, Jenkins
Git
RESTful interfaces
CI/CD

Preferred Qualifications

Effective Python, shell, and SQL programming skills.
Hands-on experience with database design and architecture in cloud data warehouses (Snowflake) and lakehouse environments (S3).
Ability to implement end-to-end encryption and decryption policies as part of sensitive data pipelines and semantic views or other data sources.
Experience across the data development lifecycle, including CI/CD and version control components and tooling (Jenkins, Git, other).
Exposure to cloud storage and orchestration tooling such as AWS and Kubernetes.
Experience with streaming interfaces and pipelines (plus).
Ability to implement data and automation services via RESTful interfaces.
Strong focus on data quality and validation within each pipeline.
Finance and accounting process experience (plus).

Location and Work Mode

Cupertino, CA (onsite)

Compensation

Base pay range: USD 149,200 to 249,000 per year
Base pay depends on skills, qualifications, experience, and location.

Benefits

Comprehensive medical and dental coverage
Retirement benefits
Discounted products and free services
Reimbursement for certain educational expenses, including tuition
Discretionary bonuses or commission payments and relocation
Apple shareholder opportunity through participation in Apple’s discretionary employee stock programs
Eligibility for discretionary restricted stock unit awards
Ability to purchase Apple stock at a discount if voluntarily participating in the Apple Employee Stock Purchase Plan

Additional Notes

At Apple, base pay is one part of a total compensation package and is determined within a range.

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Today

Senior ML Data Engineer

Apple Cupertino, CA

Cupertino, CA

Today

$185k - $325k/yr Full time Apache Airflow Artificial Intelligence Big Data

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Job Description

Build high-quality ML datasets that power visible Apple experiences. Apple’s ML Data Team within the Intelligent System Experience (ISE) group is hiring a Senior ML Data Engineer in Cupertino, CA (onsite). In this role, you will acquire, synthesize, annotate, and quality-check large-scale data pipelines that support ML and AI-centric features across products such as iPhone, iPad, Mac, Apple Watch, and AirPods.

Our team produces datasets used for training ML and AI features every year, including experiences like iPhone Lock Screen wallpapers, personalized stickers in iMessage, and Apple Intelligence capabilities such as on-device Genmoji and other visual generative models. You will also help support models used in Photos for highlighting faces and memories of loved ones.

What you’ll do

Build high-quality datasets at scale for critical Apple product features.
Acquire, synthesize, annotate, and ensure ML data quality while partnering with R&D teams across Apple’s SWE organization.
Continuously improve ML data pipelines to increase reliability, efficiency, and dataset readiness.

What we’re looking for

7+ years of industry experience as a data engineer supporting ML applications (vision domain preferred).
Bachelor’s degree in Computer Science or a related field.
Proven experience designing, automating, and scaling large data pipelines (petabyte scale desired) using modern processing technologies (examples include Iceberg, BigQuery, Airflow, and Spark).
Expertise in Python, Go, or another modern programming language, including producing high-quality, efficient code and participating in code reviews.
Strong ability to design and lead a technical roadmap, collaborate with cross-functional teams and diverse profiles, and build alignment through influence.
Demonstrated experience delivering large-scale multimodal datasets for foundation models.
Comfort operating as a self-starter in ambiguous, fast-paced environments, with the ability to identify risks, mitigate them, and secure the right people and tools to execute.
Proven track record mentoring and growing engineers, raising software engineering excellence in an ML data ops team with typically short-term delivery needs.

Tools you’ll work with

Python, Go
Iceberg, BigQuery
Airflow, Spark

Compensation and benefits

Base pay range: USD 184,700 - 324,800 per year. Base pay depends on your skills, qualifications, experience, and location.

Comprehensive medical and dental coverage
Retirement benefits
Discounted products and free services
Educational expense reimbursement (including tuition)
Discretionary employee stock programs: eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if participating in the Employee Stock Purchase Plan
Discretionary bonuses or commission payments and relocation (if eligible)

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1d ago

Machine Learning Engineer, Computer Vision

Apple Cupertino, CA

Cupertino, CA

1d ago

$150k - $278k/yr Full time Artificial Intelligence Automation Computer Vision Model Deployment

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Job Description

Apple is seeking a Machine Learning Engineer to focus on computer vision and vision-language models (VLMs) that support object understanding and recognition across Apple devices. The work centers on building models that perform reliably on real-world data and on defining evaluations that align with product quality. You will also help shape approaches that meet on-device constraints such as memory, latency, and power.

What you’ll do

Design, train, and continuously improve computer vision and VLM models for object understanding and recognition.
Strengthen model robustness for real-world conditions across devices, identifying and fixing failure modes using real data.
Define evaluation methods that reflect product quality and use them to guide model decisions.
Develop model approaches suitable for on-device constraints, including memory, latency, and power requirements.

Required qualifications

Ph.D. or Master’s in Computer Science, Machine Learning, Computer Vision, or a related field, or equivalent industry experience.
Strong foundations in computer vision and deep learning.
Proven ability to deliver end-to-end projects that cover data, training, and evaluation on real-world visual data.
Proficiency in Python and PyTorch (or an equivalent deep learning framework).
Proficiency using generative coding tools.
Rigorous experimentation skills, including clear baselines, ablations, and meaningful evaluation datasets.

Preferred qualifications

Publications in top computer vision or machine learning venues (CVPR, ICCV, ECCV, NeurIPS, ICLR), ideally with released code or work transferred to a product.
Experience in representation learning, such as self-supervised learning, metric learning, retrieval, or recognition.
Experience applying machine learning in an industry or product setting.
Experience with knowledge distillation or model compression.
Familiarity with vision-language models.

Compensation and location

Location: Cupertino, CA (onsite)
Salary: USD 150,400 - 277,600 per year

Benefits

Comprehensive medical and dental coverage
Retirement benefits
Range of discounted products and free services
Reimbursement for certain educational expenses, including tuition
Discretionary bonuses or commission payments, as well as relocation
Opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs
Eligibility for discretionary restricted stock unit awards, and ability to purchase Apple stock at a discount through voluntary participation in the Apple Employee Stock Purchase Plan

Note: Apple benefit, compensation, and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program. Base pay is one part of total compensation and is determined within a range based on skills, qualifications, experience, and location.

Tech stack

Python
PyTorch

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1d ago

Machine Learning Engineer, Evaluation

Apple Cupertino, CA

Cupertino, CA

1d ago

$185k - $325k/yr Full time Artificial Intelligence Data Analysis Data Analytics

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Job Description

Build and lead the evaluation work that helps shape global generative AI products. This role focuses on operationalizing safety and risk assessments into measurable criteria, then turning those results into reliable evidence for product ship or no-ship decisions. You will lead a team and stay hands-on with evaluation findings to improve feature safety, fairness, and user trust at scale.

What you’ll do

Provide critical technical direction to translate policy and risk assessments into clear, measurable evaluation criteria for safety and fairness.
Develop metrics to evaluate safety and fairness risks in generative models and Gen-AI features.
Design datasets, identify data needs, and expand coverage using human and synthetic generation methods.
Create sampling strategies and combine human annotation with auto-grading to generate high-quality insights efficiently at large scale.
Use and implement data pipelines and collaborate cross-functionally to run end-to-end safety evaluations.
Drive operational excellence by automating manual workflows, optimizing evaluation velocity, and scaling infrastructure for rapid product release cycles.
Distill evaluation outcomes into actionable insights for product engineering and for safety policy development.
Work with highly sensitive content, with exposure to offensive and controversial material.
Remain hands-on analyzing evaluation results, conducting failure investigations, and leveraging human and automated feedback to continuously improve feature safety.

Required experience and qualifications

Experience in Responsible AI.
Curiosity about fairness and bias in generative AI systems and a strong interest in making technology more equitable.
A Social Science or Humanities background, or other demonstrable interest in socio-technical issues.
Prior scientific research and publication experience.
Proven ability to contribute to diverse, collaborative teams.
Experience with multimodal models, agentic systems, and/or diverse languages and locales.
Experience with compliance and regulatory needs in AI, specifically related to child safety, clinical/health applications, or companionship chatbots.
Experience conducting large-scale benchmarking across models and capabilities.
Education: MS or PhD in Computer Science, Linguistics, Cognitive Science, HCI, Psychology, Mathematics, Physics, or a similar science or technology field, with a strong basis in scientific data collection and analysis, plus at least 4 years of relevant work experience (or BA/BS with 8+ years relevant experience and 2+ years directly managing engineering teams).
Experience collecting and analyzing varied language, image, voice, video, and/or multimodal data, including both human- and LLM-generated data.
Experience with LLM-Judges and human-in-the-loop methods, including designing human annotation projects and writing annotation guidelines for multi-labeled, nuanced, and sometimes conflicting data.
Proficiency in data science, machine learning, and analytics; programming with Python and Pandas; experience with at least one plotting and visualization library.
Strong cross-functional collaboration skills to prioritize competing needs, manage milestones, and communicate with stakeholders.
Rigorous approach to metric development, interpretation of evaluations, and presenting results to executives.
Comfort leading a team that works with sensitive or potentially offensive content.

Tools and technologies

Python
Pandas

Location, salary, and work model

Cupertino, CA (onsite). Salary range: USD 184,700 - 324,800 per year. Base pay is determined within the range based on skills, qualifications, experience, and location.

Benefits

Comprehensive medical and dental coverage
Retirement benefits
Range of discounted products and free services
Reimbursement for certain educational expenses, including tuition
Discretionary bonuses or commission payments as well as relocation (if eligible)
Apple shareholder opportunity through participation in Apple’s discretionary employee stock programs
Eligible for discretionary restricted stock unit awards
Ability to purchase Apple stock at a discount through voluntary participation in the Employee Stock Purchase Plan