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genai research engineer

Apple

The Health Personalization team builds outstanding technologies to support AI-driven health experiences that provide our users with understandable, actionable information about their health and wellbeing, and support them to achieve their health and wellness goals. As part of the larger Sensor Software &amp; Prototyping team, we take a multimodal approach using a variety of sensors and user data signals across hardware platforms, such as camera, wearables, and natural language user input. We are committed to building deeply personal features that understand, anticipate, and adapt to users&rsquo; behaviors and uphold Apple&rsquo;s deep commitment to privacy as a fundamental human right. Our team values expertise, innovation, and inclusivity. Come join us! 
 
Description 
 
In this role, you will develop, evaluate, and continuously improve Generative AI systems for real-world health and wellbeing applications. You&rsquo;ll apply deep expertise in health-focused machine learning alongside rigorous evaluation methodology. Your work will directly shape customer-facing health products by turning evaluation results into scalable pipelines that drive data-informed model improvements across the full ML lifecycle. You&rsquo;ll collaborate with a fast-growing team of top scientists and engineers to build generative systems that meet the highest standards of quality, reliability, and alignment with human intent.&quot;,&quot;responsibilities&quot;:&quot;Develop and improve generative AI systems for health and wellbeing applications across the full feature development lifecycle. 
 
Independently design, run, and analyze ML experiments to deliver measurable quality improvements. 
 
Design and implement evaluation frameworks-including automated assessment tools, LLM-based autograders, and benchmarks-with rigorous validation of their reliability and validity. 
 
Apply statistical and interpretability methods to analyze evaluation data and model behavior, identify failure modes through adversarial testing and failure analysis, and drive actionable improvements. 
 
Build and maintain scalable, reusable pipelines for inference, training, and evaluation, integrated with large-scale data workflows. 
 
Work cross-functionally with engineers, clinical experts, designers, and hardware and software teams to bring features into production with real-world applicability and impact. 
 
Preferred Qualifications 
 
MS or PhD in a detailed quantitative field such as computer science, mathematics, statistics, economics, health informatics, or similar and 5 years relevant industry experience 
 
Strong communication skills, comfort working with multiple engineering teams on complex projects, and experience contributing to an inclusive team culture. 
 
Technical expertise in generative AI domains, such as large language model architectures, memory representation, planning, knowledge retrieval, natural language understanding. 
 
Hands-on experience developing complex generative AI systems in an applied setting, e.g. experience with post-training techniques like supervised fine-tuning, adapter training, and reinforcement learning from human feedback. 
 
Experience with LLM-based evaluation systems and rigorous, evidence-based approaches to test development, e.g. quantitative and qualitative test design, reliability and validity analysis. 
 
Customer-focused mindset with experience or strong interest in building consumer digital health and wellness products. 
 
Knowledge of health informatics or experience with complex health data sources (e.g. EHRs, medical ontologies, wearables) 
 
Experience with building and deploying performant and scalable systems (full-stack) 
 
Minimum Qualifications 
 
BS and a minimum of 10 years relevant industry experience 
 
Proficiency in Python and ability to write clean, performant code and collaborate using standard software development practices. 
 
Technical expertise and hands-on experience crafting and evaluating machine learning solutions for user-facing applications. 
 
Experience applying a scientific approach to drive machine learning innovation: developing hypotheses, designing experimentation strategies, and guiding data generation / collection / evaluation (e.g. user studies, annotation workflows, A/B tests). 
 
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.

GenAI Research Engineer

The Intelligence Platform team empowers clients across Apple&rsquo;s operating systems with a high quality user-centric search and data platform, and the primary inference platform that enable next generation user experiences for Apple Intelligence. We are in search of an accomplished and driven Machine Learning Engineer who has a robust understanding of Large Language Models, Generative AI and high-performance systems computing. Your primary role will involve working with our cross-functional teams that build foundation models, as well as our client teams that want to run inference using these models and continue the development of our inference stack. By contributing to our team, you&rsquo;ll play an integral part in developing Siri, Photos, Music, and various other services, leaving a significant footprint on the evolution of our AI platforms. Join us in our exciting journey as we push the frontiers of Machine Learning and Generative AI. Your expertise and contributions will be invaluable in shaping the future of our Intelligence Platform. 
 
Description 
 
As a Machine Learning Engineer on the Apple Intelligence Platform Inference Tean, you&rsquo;ll join a phenomenal team of top-performing engineers and and will be entrusted with a range of responsibilities. Your tasks will include: 
 
Leading the exploration and application of Large Language Models and Generative AI, venturing into new areas within these fields. 
 
Translating the latest research into high-performing systems and a model serving stack that can be practically applied to enhance user experiences. 
 
Contribute to setting the team&rsquo;s strategic direction, cultivating an environment that encourages innovation and professional growth. 
 
Collaborating with various teams to develop and implement evolving requirements of our clients on the GenAI inference stack, ensuring performance optimization and alignment with broader business goals. 
 
Preferred Qualifications 
 
An advanced degree (Master&rsquo;s or Ph.D.) in Computer Science, Artificial Intelligence, Machine Learning, or a related field is required 
 
Ongoing professional development in Machine Learning and Artificial Intelligence domains is expected. 
 
Minimum Qualifications 
 
In-depth experience in Machine Learning, with a particular emphasis on Large Language Models (LLMs) and Generative AI. 
 
Published research in the field of Machine Learning or AI is highly desirable, indicating an ability to not only understand but also contribute to cutting-edge research. 
 
Proven ability to comprehend, interpret, and apply cutting-edge research into tangible applications. 
 
Proven problem-solving and leadership abilities, with the capacity to steer the team&rsquo;s research and practical applications in a collaborative and fast-paced environment. 
 
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.

Machine Learning Engineer - Large Language Models & Generative AI Inference

Imagine what we could do together. At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job, and there&rsquo;s no telling what we could accomplish! 
 
The Apple Services Engineering team is one of the most exciting examples of Apple&rsquo;s long-held passion for combining art and technology. We are the people who power the App Store, Apple TV, Apple Music, Apple Podcasts, Apple Books, Apple Sports and Apple Fitness. And we do it on a massive scale, meeting Apple&rsquo;s high standard for quality and excellence, to deliver a huge variety of entertainment in over 50+ languages to more than 150 countries. 
 
Description 
 
The App Store team powers the data backbone behind discovery, search, trust and safety, developer insights, and experimentation across billions of daily user interactions. We ingest, model, and activate high-volume event data in near real time with uncompromising standards for privacy, reliability, and latency. As a Senior Software Engineer, you will design and operate large-scale distributed systems and build production-grade Generative AI applications that make App Store signals useful, safe, and actionable for teams across the Apple. &quot;,&quot;responsibilities&quot;:&quot;Architect and operate petabyte-scale App Store pipelines with strict SLAs. 
 
Define event taxonomies, schemas, and governance to ensure durable contracts, lineage, and high-quality metadata. 
 
Ship privacy-by-design processing: PII minimization, consent enforcement, differential privacy, and edge-friendly patterns. 
 
Build production GenAI services with App Store context: embeddings, vector search, RAG, prompt orchestration, guardrails, and automated evals. 
 
Lead incident response and root-cause analysis; automate backfills, reprocessing, and lineage-aware rollbacks. 
 
Mentor engineers, influence architectural roadmaps, and improve on code quality, testing, performance, reliability, and documentation. 
 
Preferred Qualifications 
 
Familiarity shipping GenAI apps to production: embeddings, vector DBs, RAG, prompt orchestration. 
 
Excellent communication and collaboration skills; ability to influence multi-functional partners and drive complex projects to completion. 
 
Minimum Qualifications 
 
8+ years of hands-on software engineering experience building large-scale data systems. 
 
Strong programming skills in one or more of Scala and Java. 
 
Hands-on expertise with distributed data systems such as Spark, Kafka, Hadoop, Flink. 
 
Solid foundation in data storage and SQL : (S3/HDFS/Parquet), and lakehouse tables (Iceberg/Delta/Hudi). 
 
Solid systems fundamentals: algorithms, data structures, concurrency, consistency, caching, and observability. 
 
Built and operated services with Docker/Kubernetes, automated CI/CD and low-latency inference systems. 
 
BS/MS/PhD in Computer Science or related field, or equivalent 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, App Store Data

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

At Apple, we work every day to craft products that enrich people's lives. If you're passionate about taking on unsolved challenges, we have a great opportunity for a results-oriented and highly motivated RTL Design Engineer. This is an exciting position in the world class Apple mixed-signal silicon design team! 
 
This role will build upon your solid foundation in digital logic circuits while introducing mixed-signal and analog circuit design and features. You will work with a variety of flows fundamental to modern silicon engineering: modeling and integrating high-performance mixed-signal and analog IPs into high-speed digital circuits, ensuring formal equivalence between custom designs and their abstract representations. This is an excellent opportunity to gain valuable experience in software methods and analysis, which are increasingly crucial across the semiconductor industry. 
 
As a member of our dynamic team, you will have the exceptional opportunity to help create the next generation of products that will delight and inspire millions of Apple customers every day. You will work to specify, design, verify, and support lab bring-up of sophisticated digital and mixed-signal circuits with signal processing capabilities. 
 
Description 
 
In this role, you will be responsible for specifying and/or micro-architecting digital and signal processing blocks in sophisticated mixed-signal circuits. You will be responsible for RTL coding of blocks specified by you or others, including implementation of DSP algorithms. You will also participate in the design verification and bring-up of such blocks by writing meaningful assertions, debugging code, and otherwise interacting with the design verification team. You will contribute to the lab bring-up of those circuits by potentially writing test scripts, analyzing lab data, proposing experiments, and validating signal processing performance.&quot;,&quot;responsibilities&quot;:&quot;RTL Design &amp; Implementation: Develop and optimize RTL code in Verilog/SystemVerilog for mixed-signal digital blocks and signal processing pipelines 
 
DSP Algorithm Translation: Collaborate with algorithm engineers to translate DSP concepts (filtering, transforms, modulation, signal analysis) into efficient, high-performance RTL implementations 
 
Design Verification: Write comprehensive assertions, unit-level testbenches, and participate in functional verification using industry-standard methodologies 
 
Integration &amp; Bring-up: Partner with cross-functional teams to integrate complex IPs, validate performance in silicon, and support lab characterization 
 
Collaborative Problem-Solving: Work effectively with analog designers, algorithm engineers, verification specialists, and system architects across disciplinary boundaries 
 
Preferred Qualifications 
 
Front-end tools expertise (Verilog simulators, linters, clock-domain crossing checkers) 
 
Synthesis, static timing analysis, and design-for-test (DFT) 
 
SystemVerilog assertions, checkers, and advanced verification techniques 
 
Scripting languages (Perl, Python) 
 
Formal verification and low-power design methodologies 
 
Hardware-software co-design and system-level optimization 
 
Hands-on DSP experience: signal processing concepts, RTL algorithm implementation, hardware optimization techniques (pipelining, parallelization, resource sharing) 
 
Intermediate to advanced GenAI proficiency: Using AI tools for SystemVerilog design, validation, optimization, and understanding GenAI capabilities/limitations in hardware design 
 
Minimum Qualifications 
 
Bachelors of Science in Electrical Engineering. 
 
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 $126,800 and $220,900, 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.

RTL Design Engineer

At Apple, we focus deeply on our customers&rsquo; experience. Apple Ads brings this same approach to advertising, helping people find exactly what they&rsquo;re looking for and helping advertisers grow their businesses. 
 
Our technology powers ads and sponsorships across Apple Services, including the App Store, Apple News, and MLS Season Pass. Everything we do is designed for trust, connection, and impact: We respect user privacy, integrate advertising thoughtfully into the experience, and deliver value for advertisers of all sizes-from small app developers to big, global brands. Because when advertising is done right, it benefits everyone. 
 
Description 
 
As a Data Site Reliability Engineer in Apple Ads, you will focus on designing, building, and managing cloud-based systems and infrastructure that stores, process, transforms and analyzes large datasets. You will ensure data and corresponding infrastructure is accessible, reliable, and secure within the cloud environment, working with various Apple Internal and 3rd party cloud providers like AWS.&quot;,&quot;responsibilities&quot;:&quot;Your high-level responsibilities will include: 
 
Design, build and manage large scale distributed data systems on AWS using services such as EMR, EKS, MSK. 
 
Design and develop internal tooling and automation frameworks to improve data infrastructure reliability, cost-efficiency, and operational visibility. 
 
Collaborate with cross-functional engineering teams like advertising, machine learning and data platforms to define infrastructure architecture, troubleshoot complex issues, and drive production excellence. 
 
Lead initiatives to eliminate toil via automation, improve efficiency and scalable deployment patterns. 
 
Contribute to strategic decision making related to adoption of a multi-cloud echo system to maintain operational excellence on the current stack while still enabling the path for future innovation. 
 
Preferred Qualifications 
 
Proven experience as a committer to open-source projects like Apache Spark, Flink, etc 
 
Track record of driving automation, cost optimization and performance tuning at scale for data systems. 
 
Experience leveraging ML and GenAI capabilities to improve infrastructure and Operational efficiency is a plus. 
 
Experience driving adoption of new technologies and influencing designing of systems. 
 
Strong programming skills on object-oriented, functional or procedural programming languages, preferably Java / Scala / Kotlin / Python 
 
Experience designing and managing Infrastructure as Code with Helm and CRD, ensuring repeatable, secure, and scalable deployments. 
 
Minimum Qualifications 
 
5+ years of experience in Site Reliability Engineering with a strong focus on building, scaling and operating cloud based distributed data systems. 
 
Proven expertise running cloud infrastructure built on managed services offered by cloud providers like AWS 
 
Strong technical grasp and experience working on Open Source technologies designed for large scale data processing, like Apache Spark, Flink, Kafka, Iceberg, etc. 
 
Big Data processing and storage systems (streaming and batch) 
 
Strong expertise and experience with container orchestration systems like Kubernetes 
 
Experience designing, analyzing and troubleshooting large-scale distributed systems. 
 
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 Site Reliability Engineer (SRE), Data - Apple Ads

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 58+ Genai research engineer in Cupertino this April. Find roles across top companies and apply now to boost your career.