aiml - sr machine learning engineer - data and ml innovation

aiml - sr machine learning engineer, data and ml innovation

aiml - sr machine learning engineer, modeling evaluation & data

administrative assistant, hardware technology

ai researcher

ai/ml engineer, applied data science Jobs in Cupertino

ai/ml engineer, applied data science

aiml - sr machine learning engineer - data and ml innovation Jobs in Cupertino

aiml - sr machine learning engineer, data and ml innovation Jobs in Cupertino

aiml - sr machine learning engineer, modeling evaluation & data Jobs in Cupertino

senior data scientist

Apple

We&rsquo;re looking for a Senior Software Engineer to help build the next generation of large-scale data systems that power high-impact decisions across Siri. In this role, you'll operate at the intersection of engineering excellence and business impact. You&rsquo;ll design and implement scalable, reliable systems to transform raw data into actionable insights for leadership. This is a high-visibility, high-impact position with the opportunity to influence the direction of products and strategy. 
 
The Siri User Experience Metrics team is at the heart of shaping how users interact with Siri every day. We use data, metrics and insights to continuously improve Siri&rsquo;s User Experience across Apple platforms including iOS, macOS, visionOS, tvOS and watchOS. 
 
Our team defines and owns the most critical user facing metrics, identifies quality issues, builds scalable reporting tools and delivers actionable insights that directly inform product decisions. We collaborate closely with product, platform and feature teams to ensure Siri not only works - but delivers exceptional User Experience. From response time to failure tracking, we make sure Siri feels fast, natural and helpful wherever users need it. 
 
As a Senior Software Engineer on the Siri User Experience Metrics team, you will have significant influence and responsibility in identifying and alert on quality issues using data and metrics to shape Siri&rsquo;s User Experience. 
 
If this sounds like you, you're someone who&rsquo;s laser-focused on impact - bringing sharp programming skills, strong problem-solving abilities and clear communication to the table, all driven by a passion for building exceptional products. 
 
You'll have the opportunity to drive meaningful impact across all Apple platforms by collaborating closely with Engineering, Product, Testing and Quality teams. Your work will directly enhance the Siri experience for billions of users - shaping how people interact with Apple every day. 
 
Description 
 
Join us in building the data backbone of Siri&rsquo;s regression detection system - the platform that enables engineering teams and senior leadership to see, understand, and improve product quality. In this role, you&rsquo;ll build large-scale data systems that power metrics observability at scale. Success in this role means not only technical excellence, but also the ability to collaborate across teams, communicate effectively and align diverse stakeholders around solving complex, high-impact challenges. 
 
You thrive in fast-paced, dynamic environments and are comfortable navigating ambiguity to deliver meaningful, incremental impact. You bring strong problem-solving skills, operate with a high degree of autonomy and have a track record of executing effectively. With a commitment to continuous learning and attention to detail, you actively seek opportunities to innovate and share knowledge. You follow engineering best practices - including unit testing, CI/CD, documentation, monitoring, and alerting - to ensure reliable, maintainable solutions. In this role, you&rsquo;ll collaborate closely with stakeholders to understand metric needs, provide technical guidance, gather requirements and deliver robust data solutions and intuitive dashboards. 
 
Preferred Qualifications 
 
Experience supporting the end-to-end machine learning lifecycle, including data ingestion, feature pipelines, batch inference, and model monitoring in production environments. 
 
Hands-on experience building, scheduling, and maintaining data and ML workflows using orchestration frameworks such as Apache Airflow 
 
Experience working in cloud environments (AWS, GCP, or Azure) and integrating data pipelines with cloud-native storage and compute services 
 
Minimum Qualifications 
 
7 years of development experience and Bachelors or Masters degree in Computer Science or related field or 5 years development experience and PhD in Computer science or related field. 
 
Expert knowledge of one or more object-oriented programming languages (Java, Objective-C, C++, Scala, Swift etc) or scripting languages (Python, Ruby, Bash etc.). 
 
Experience working with Spark or other distributed data technologies (e.g. Hadoop, Presto, Flink, Druid) for building efficient and large scale data systems. 
 
Expertise in development of big data systems and ETL for product metrics and analysis of large data volumes to identify patterns, draw insights and troubleshoot issues. 
 
Knowledge of SQL to analyze data, derive insights and drive improvements. 
 
Leadership experience, including being a technical lead for complex, cross functional development projects demonstrating good technical judgement and prioritization skills. 
 
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 $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. 
 
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

Sr Software Engineer, Siri User Experience Metrics and Data

We are looking for a Senior Software Engineer to join our Data Engineering Infrastructure team, which builds and operates the foundational platforms that power data ingestion, transformation, and analytics across the organization. You will design and develop high-performance, reliable, and scalable systems that enable data engineers, analysts, and ML practitioners to move, process, and govern data efficiently and securely. 
 
Description 
 
As a Senior Software Engineer in the Data Engineering Infrastructure team, you will design and build distributed systems and frameworks that automate the lifecycle of data - from ingestion to transformation to serving. You&rsquo;ll work at the intersection of software engineering, distributed data processing, and cloud infrastructure, helping to define the standards, abstractions, and tools that enable our data platform to operate at scale. 
 
You will collaborate closely with teams across data engineering, analytics, ML, and platform engineering to deliver resilient infrastructure components such as data ingestion pipelines, metadata and schema management services, workflow orchestration, and monitoring frameworks. This is a hands-on role where you will influence architecture, write production-grade code, and drive engineering excellence across the data platform.&quot;,&quot;responsibilities&quot;:&quot;Design, build, and maintain scalable data infrastructure and frameworks supporting batch and streaming workloads. 
 
Develop common services for data ingestion, schema evolution, metadata management, and data quality enforcement. 
 
Implement automation for data pipeline deployment, monitoring, and governance. 
 
Collaborate with data engineers and platform teams to define APIs, SDKs, and libraries that make developing data applications simpler and safer. 
 
Improve performance, reliability, and observability of data pipelines and platform components. 
 
Participate in architecture reviews, code reviews, and technical design discussions. 
 
Drive adoption of best practices in distributed systems, storage formats (Parquet, Iceberg), and data access layers. 
 
Contribute to capacity planning, cost optimization, and operational excellence in cloud and on-prem environments. 
 
Mentor junior engineers and contribute to the overall technical strategy and roadmap for the data platform. 
 
Preferred Qualifications 
 
Deep expertise in optimizing and troubleshooting distributed data frameworks (e.g., Apache Spark internals, Flink stateful streaming, Kafka Connect) 
 
Advanced experience with workflow orchestration tools (e.g., Airflow, Prefect, Dagster), including custom development 
 
Proven track record in performance tuning, cost optimization, and designing comprehensive observability solutions for large-scale cloud data platforms 
 
Familiarity with data security, privacy, and compliance principles within data infrastructure 
 
Experience integrating data platforms with MLOps and machine learning workflows 
 
Active participation or contributions to relevant open-source data technologies or industry communities 
 
Master&rsquo;s or Ph.D. degree in Computer Science, Data Engineering, or a related quantitative field 
 
Minimum Qualifications 
 
12+ years of experience in software engineering, with at least 5 years focused on data systems or platform infrastructure 
 
Proven track record of leading design discussions, mentoring engineers, and driving cross-team technical initiatives 
 
Strong programming skills in Java, Python; Scala - nice to have 
 
Hands-on experience designing, developing, and operating high-performance backend services 
 
Hands-on experience with distributed data frameworks such as Spark, Flink, or Kafka 
 
Solid understanding of data modeling, storage formats (Parquet/Avro/ORC), and partitioning strategies 
 
Experience with data governance, cataloging, and schema management systems (e.g., Hive Metastore, Glue, Iceberg, Delta Lake) 
 
Experience working with cloud-based data platforms (AWS, GCP, or Azure) 
 
Experience building data infrastructure frameworks, SDKs, or shared libraries used by multiple data teams 
 
Familiarity with CI/CD, container orchestration (Kubernetes), and infrastructure-as-code tools (Terraform, CloudFormation) 
 
Excellent problem-solving, debugging, and communication skills 
 
Bachelor&rsquo;s degree in Computer Science, Engineering, or related field (or equivalent practical 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 $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. 
 
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

Senior Software Engineer - Data

Do you want to play a part in the revolution in Foundation Models? Contribute to model hillclimbing for Apple Intelligence features that leverage Apple Foundation Models, and work with the people who built the intelligent products that helps millions of people get things done - just by asking or typing? 
 
The vision for AIML FM Data organization is to improve Foundation Models by leveraging data and cutting-edge LLM techniques. As a Sr ML Engineering on the team, you will drive ML innovations, identify key opportunity areas and experiment with various techniques to improve model training and evaluation efficiency and performance. 
 
Description 
 
As a Senior Machine Learning Engineer, you will join end-to-end development of large language models and agentic systems, from training pipelines to evaluation frameworks and production deployment. 
 
You will work at the intersection of modeling, infrastructure, and product, helping push model quality through systematic experimentation and iteration. 
 
You&rsquo;ll collaborate closely with research, infrastructure, and product teams to design robust training pipelines, build agent environments, and ship high-impact AI capabilities into real-world applications. 
 
This role blends deep modeling expertise with strong engineering fundamentals and offers the opportunity to shape both the technical direction and the ML platform powering Apple products.&quot;,&quot;responsibilities&quot;:&quot;Model Training &amp; Optimization 
 
Design and implement large-scale LLM pretraining and post-training pipelines, including supervised fine-tuning, preference optimization, and continual learning. 
 
Drive model hillclimbing through disciplined experimentation: dataset curation, hyperparameter tuning, and ablation studies. 
 
Work on scalable training workflows using distributed frameworks. 
 
Evaluation, Reward, and Data Systems 
 
Develop evaluation frameworks for both offline benchmarks and online metrics, covering reasoning, tool use, and task success. 
 
Design and maintain verifiers / rubric-based reward systems for agentic tasks and model alignment. 
 
Build data pipelines for data generation, filtering, labeling, and replay buffers. 
 
Agent &amp; Environment Infrastructure 
 
Build and maintain agent training environments, including tool APIs, simulators, and sandboxed runtimes. 
 
Implement environment abstractions to support reinforcement learning and agent evaluation at scale. 
 
Collaborate on large scale RL-infra: RL-trainer, rollout system, and containerized environments. 
 
Preferred Qualifications 
 
Direct experience with agentic systems, including tool use, environment design, or reinforcement learning. 
 
Experience with building or operating training environments or simulators (gym-style, tool-based, or sandboxed environments). 
 
Experience with model hillclimbing workflows: systematic experimentation, ablations, dataset iteration, and continuous quality improvement. 
 
Ability to work across research and engineering boundaries, turning ideas into scalable systems. 
 
Have demonstrated creative and critical thinking with an innate drive to improve how things work. Have a high tolerance for ambiguity. 
 
Minimum Qualifications 
 
5+ years of hands on ML engineering experiences, with at least 1+ years working directly on large language models or generative AI. 
 
Bachelor&rsquo;s, Master&rsquo;s, or PhD in Computer Science, Machine Learning, or a related technical field - or equivalent practical experience. 
 
Hands-on experience with LLM training workflows, including one or more of: Pretraining or continued pretraining, Supervised fine-tuning (SFT), Preference optimization (e.g., RLHF, DPO, PPO). 
 
Strong software engineering fundamentals: debugging, testing, code reviews, and production reliability. 
 
Demonstrated publication records in relevant conferences (e.g., NeurIPS, ICML, ICLR, etc.). 
 
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

As part of the work on machine-generated dialog we are developing novel measurements of its quality. These include cutting-edge llm-judges for aspects like groundedness (lack of hallucinations), Siri Tone and Style (a suite of Design requirements), Safety, and others. 
 
Description 
 
To measure our progress on this front, we need to track the state of our dataset composition, accuracy of llm-judges, human expert review results in a central and visual representation. A DRI for Metrics and Reporting will:&quot;,&quot;responsibilities&quot;:&quot;Build an easy to use dashboard for our datasets - requires integration with other teams 
 
Build dashboards to visualize our status 
 
Help define useful metrics 
 
Build tools to facilitate processing of human review results (inter-annotator agreement, storage, selection of the most useful data points for human expert review) 
 
Build tools and pipelines to streamline quality measurement processes 
 
Preferred Qualifications 
 
Experience with writing and architecting production level code 
 
Deep understanding of Machine Learning concepts 
 
Experience in Model training and/or evaluation 
 
Good engineering practices to create sustainable and easy to use metric reporting pipelines 
 
Attunement to computational linguistics, language quality is a plus 
 
Minimum Qualifications 
 
M.S. or Ph.D. in Computer Science, Data Science, Data Engineering 
 
3+ years in data-science and/or data-engineering (iceberg, pandas python, Tableau or equivalent, data collection and visualization) 
 
2+ years of python coding 
 
Good understanding of metrics, crowd science, annotation analysis, statistics 
 
Ability to work independently and cross-functionally to integrate in partner team reporting systems and pipelines 
 
Excellent communication skills and the ability to thrive in a highly collaborative work environment 
 
Good engineering practices to create sustainable and easy to use metric reporting pipelines 
 
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 $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. 
 
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

Sr. Data Science Engineer, Siri Core Modeling

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

<div>Imagine what you could do here. 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. Join Apple, and help us leave the world better than we found it. 
 
The Data Solutions &amp; Initiatives (DSI) team supports Apple&rsquo;s business leaders as they project, manage, and report on business performance. We do this by driving vast improvements for our customers, experiences that delight, platforms that scale to meet the demands of the business, tools that provide crucial productivity and insights. 
 
Description 
 
This is a senior front-end engineering role. You will collaborate closely day-to-day with product managers, UX designers and other engineers to plan, design, build and deliver high quality user-facing and interactive web applications. 
 
Your responsibilities will include: 
 
<ul><li>Lead and build front-end systems, making key web-based decisions that improve user experience, performance, scalability, and accessibility</li></ul> 
<ul><li>Own UI architecture and drive best practices in linting, testing, patterns/paradigms, documentation, processes, etc.</li></ul> 
<ul><li>Design and build high-quality, reusable web components and libraries to ensure a consistent, beautiful UI/UX across our products</li></ul> 
<ul><li>Collaborate with cross-functional partners to deliver high-quality web applications</li></ul> 
<ul><li>Contribute to the full web application lifecycle, from debugging complex production issues to implementing robust, long-term solutions</li></ul> 
<ul><li>Mentor and coach less experienced engineers, fostering a culture of collaboration, innovation, and continuous learning</li></ul> 
<ul><li>Research novel technologies, building proofs of concept and presenting learnings</li></ul> 
<ul><li>Promote and exemplify technical excellence and innovation</li></ul> 

Preferred Qualifications 
 
10+ years of front-end engineering experience 
 
Proficiency with native development (iOS, macOS, Swift) 
 
Hands-on expertise in API development and database design 
 
Cloud platform expertise for deploying scalable, reliable solutions 
 
Proven hands-on experience in rapid scaling, performance and resilience testing 
 
Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science or equivalent experience 
 
Minimum Qualifications 
 
7+ years of experience building and maintaining high-performant, responsive and user-friendly front-end systems 
 
Expert in HTML5, CSS, and JavaScript, with mastery of at least one modern framework (React, Angular, Vue, or Svelte) 
 
Working knowledge of API development and cloud-based CI/CD deployment 
 
Comprehensive knowledge of front-end stack fundamentals, performance optimization techniques and security 
 
Strong UX/UI design understanding with a creative eye for visual details that deliver intuitive user experiences 
 
Strong communication skills to effectively convey technical concepts 
 
Ability to guide teams through iterative planning, execution, and delivery processes 
 
Strong understanding of designing for resilience and self-healing capabilities 
 
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 $181,100 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.</div>

Senior Front-End Engineer, Data Solutions & Initiatives

We build frontier foundation models that power intelligent experiences at Apple. Our team works across the full training lifecycle: including pre-training foundation models, and developing mid-training approaches that bridge general capability and task-specific performance. What makes our work distinct is that we're engineering models specifically for Apple silicon and optimized for experiences that are private, personal, and deeply integrated into the OS. We're solving frontier problems in reward modeling to resist reward hacking, handling sparse and delayed rewards in agentic settings, and aligning models reliably across the spectrum from open-ended creative tasks to precise, action-taking workflows. If you're drawn to hard problems where the research and the product are inseparable, this is the team. 
 
Description 
 
This position operates at the convergence of Software Engineering and Machine Learning Research. Unlike traditional backend roles, this position requires you to design systems where the outcome is the statistical distribution and quality of data itself. You will work alongside Research Scientists to transform theoretical observations into concrete, scalable engineering solutions. Your core focus will be the architecture of our Data Acquisition, Processing, and Repository Management systems for Large Model training. You will lead technical efforts to enable active, quality-driven data curation, including filtering, deduping, synthetic data generation and data mixing, ensuring our models are trained on the highest-quality information available.&quot;,&quot;responsibilities&quot;:&quot;Architect Scalable Ingestion Systems: Design and implement high-throughput distributed systems to ingest petabytes of text and multimodal data from diverse sources, including web crawls and third-party partnerships. 
 
Repository Optimization: Manage the lifecycle of large-scale datasets across data storage and high-performance file systems. Optimize data formats for efficient random access and sequential scanning during model training. 
 
Data Governance &amp; Privacy: Engineer robust data governance and privacy solutions for the training data, in collaboration with compliance and legal teams, to ensure adherence to stringent regulatory standards. 
 
High-Performance Processing Pipelines: Build and maintain distributed data processing workflows using advanced frameworks on cloud infrastructure (e.g., GCP, AWS). 
 
Algorithmic Data Curation: Implement sophisticated data filtering and selection logic to remove low-quality content. Develop semantic deduplication at scale to prevent model memorization and improve training efficiency. 
 
Decontamination Removal: Design automated systems to detect and remove benchmark leakage, ensuring that evaluation datasets remain strictly isolated from training corpora. 
 
Infrastructure for Scaling Laws: Collaborate with researchers to enable data ablations and scaling experiments. Build tools to support systematic data mixture optimization and empirically data studies. 
 
Preferred Qualifications 
 
Research Collaboration: Experience working within or closely with ML research organizations (e.g., as a Research Engineer), with an ability to translate research results into engineering implementations. 
 
Domain Knowledge: Familiarity with lifecycle of modern LLM training, end-to-end workflows, and underlying system architecture. 
 
Complex Data Types: Experience in processing complex data modalities beyond plain text, such as source code repositories, images, videos, and audios. 
 
Minimum Qualifications 
 
Education: Bachelor&rsquo;s degree in Computer Science, Electrical Engineering, or Mathematics. 
 
Technical Expertise: 4+ years of software engineering experience with a specific focus on Data Infrastructure, Distributed Systems, or AI/ML Engineering. 
 
Language Proficiency: Expert fluency in Python, and strong competence in system languages such as C++. 
 
Cloud Architecture: Extensive experience architecting solutions on major public cloud platforms (e.g. GCP) to build scalable data systems (e.g. with Apache Beam, GCS) 
 
Performance Engineering: Deep experience profiling and optimizing high-throughput data systems. Demonstrated ability to debug distributed bottlenecks (e.g., stragglers, I/O saturation), optimize data formats and provide efficient data storage solutions. 
 
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 $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. 
 
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

Senior Research Engineer, Training Data Infrastructure in Foundation Models

Explore 80+ Senior data scientist in Cupertino this April. Find roles across top companies and apply now to boost your career.