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Apple

Apple is where individual imaginations gather together, committing to the values that lead to great work. Every new product we build, service we create, or Apple Store experience we deliver is the result of us making each other&rsquo;s ideas stronger. That happens because every one of us shares a belief that we can make something wonderful and share it with the world, changing lives for the better. It&rsquo;s the diversity of our people and their thinking that inspires the innovation that runs through everything we do. When we bring everybody in, we can do the best work of our lives. Here, you&rsquo;ll do more than join something - you&rsquo;ll add something. 
 
As part of Apple&rsquo;s central data annotation engineering team, you&rsquo;ll help build the next generation of AI-powered user experiences. Our work provides high-quality datasets and expert feedback to train machine learning models and evaluate their performance across all products and verticals. The team maintains and develops a global distributed system that captures insights from human domain experts and analysts worldwide, operating at a scale that few companies can match. We leverage cutting-edge human-in-the-loop algorithms to create and curate datasets through fine-tuned multi-step annotation workflows and near real-time data quality feedback signals. You&rsquo;ll tackle complex challenges in ML data quality at unprecedented scale while collaborating closely with AIML engineering teams across the company. From Siri to the Photos app, from iPhone to Vision Pro, you&rsquo;ll help bring innovative experiences to millions of users worldwide. 
 
Description 
 
This role focuses on enhancing the annotation quality capabilities of Apple's central data annotation platform. You'll work on a cloud-based system that supports machine learning model development across all Apple products. The position combines backend engineering with research and concept development to improve how we measure, monitor, and optimize annotation and ML dataset quality at scale. You'll be responsible for building systems that ensure high-quality training data while developing innovative approaches to quality assessment and feedback mechanisms. 
 
As part of a close-knit team of half a dozen engineers focused on annotation quality initiatives and embedded in an even larger team of fellow data annotation engineers, you'll collaborate on shared challenges and contribute to collective problem-solving efforts. The team works together on overlapping projects, combining individual expertise in backend and frontend engineering, statistics, and ML to advance the state of annotation quality measurement and optimization. You'll have the opportunity to learn from peers tackling similar technical problems while contributing your own insights to push the boundaries of what's possible in large-scale data quality assessment. 
 
Your contributions will directly impact the foundation of Apple's AI and machine learning capabilities, ensuring that models across the entire product ecosystem are trained on the highest quality data possible.&quot;,&quot;responsibilities&quot;:&quot;Develop and maintain backend services for annotation quality measurement and monitoring systems 
 
Design and implement statistical measures and algorithms to assess annotation quality across diverse datasets incl. both foundational model driven and traditional approaches 
 
Create automated quality feedback mechanisms that provide real-time insights to annotation teams 
 
Research and prototype new approaches for improving annotation consistency and accuracy 
 
Optimize and design efficient data pipelines for dataset/annotation quality metrics collection 
 
Preferred Qualifications 
 
5+ years of experience in data annotation, data quality, or related ML value chain roles 
 
Experience building and scaling web-based platforms for machine learning workflows 
 
Advanced knowledge of statistical methods for data quality assessment 
 
Experience with distributed systems and microservices architecture 
 
Background in annotation workflow optimization 
 
Track record of research publications or patents in data quality or machine learning 
 
Experience working in cross-functional teams with both technical and non-technical stakeholders 
 
Minimum Qualifications 
 
PhD in Computer Science, Machine Learning, Statistics, Math, Physics or related field, or 5 years of equivalent work experience 
 
3+ years of backend engineering experience with cloud-based services 
 
Proficiency in Python and/or Golang for backend development 
 
Experience with AWS services including Lambda and RDS/Aurora 
 
Strong foundation in applied statistics and machine learning fundamentals 
 
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.

AIML - Applied ML Engineer, Data Generation & Verification

We&rsquo;re building the next generation of AI evaluation systems - and we&rsquo;re looking for a 
 
motivated early-career engineer who&rsquo;s excited to work at the intersection of ML, 
 
software, and product. You&rsquo;ll join a team focused on making AI systems - including 
 
LLMs and agentic AI - more measurable, testable, and trustworthy in real-world 
 
scenarios. 
 
This is a hands-on, collaborative role ideal for someone with a strong foundation in 
 
software engineering and machine learning, and an eagerness to grow by building tools 
 
and systems that help evaluate advanced AI behavior at scale. 
 
Description 
 
As an Applied ML Engineer on our team, you&rsquo;ll help develop simulation systems, 
 
support data tooling, and contribute to evaluation workflows that improve the reliability 
 
of modern AI. You&rsquo;ll collaborate closely with experienced engineers and researchers, 
 
learning how to instrument, monitor, and analyze model behavior - especially for 
 
language models and agent-style systems. 
 
This is a great opportunity for someone early in their career to work with cutting-edge AI 
 
technologies in a high-impact, supportive environment. You&rsquo;ll gain experience working 
 
with large-scale ML systems, learn best practices in applied AI, and grow your skills 
 
across engineering, product, and research.&quot;,&quot;responsibilities&quot;:&quot;Contribute to systems that simulate interactive behaviors (including LLM-driven 
 
agents) 
 
Help build tools to support dataset generation and evaluation workflows 
 
Assist in developing pipelines for structured insights from model behavior 
 
Collaborate with teammates to debug and improve evaluation systems 
 
Write clean, testable code to support scalable and reliable infrastructure 
 
Learn how to define metrics that connect model behavior to real-world outcomes 
 
Preferred Qualifications 
 
Coursework or internship experience in ML, AI systems, or applied data science 
 
Familiarity with training or evaluating models (even via coursework or personal 
 
projects) 
 
Exposure to tools like PyTorch, TensorFlow, or Hugging Face 
 
Interest in AI observability, behavior simulation, or synthetic data 
 
Passion for working cross-functionally in fast-moving, exploratory teams 
 
Minimum Qualifications 
 
Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Machine Learning, or related field 
 
Strong programming skills in Python or another modern language (e.g., Java, Swift, 
 
Go) 
 
Basic understanding of machine learning principles 
 
Interest in LLMs, generative AI, or agent-based systems 
 
Curiosity about how to evaluate and improve real-world AI performance 
 
Strong collaboration and communication 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 $120,300 and $210,100, 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.

Applied ML Engineer - AI/ML Evaluation & Simulation

The Applied Machine Learning team builds production multimodal systems that understand and transform large-scale image, audio, and video content. Our work spans diffusion-based image generation, transcription and diarization, face and object detection, OCR and image description for search, and automated quality control of media pipelines. 
 
We are looking for a Staff Machine Learning Engineer to strengthen our diffusion and video models, adapt small and mid-sized LLMs, and turn our uniquely large corpus of weakly labeled media into a durable product advantage. This is an opportunity to shape the next generation of multimodal experiences end-to-end, from data and models to evaluation and user impact. 
 
Description 
 
The Staff Machine Learning Engineer - Multimodal Generation &amp; Post-Training will be a senior individual contributor on a small, applied ML team focused on production multimodal systems. The role will lead fine-tuning and adaptation of diffusion and emerging video models, as well as post-training of small and medium LLMs for captioning, moderation, and retrieval-friendly descriptions. 
 
The engineer will design data and evaluation workflows that use our large archive of weakly labeled music, podcast, film, TV, and short-form content to drive measurable quality and efficiency improvements. The role includes close collaboration with partner infra teams for model serving and with adjacent product and research groups to bring new capabilities into production. 
 
Preferred Qualifications 
 
PhD in Computer Science, Machine Learning, or a related technical field. 
 
8+ years of industry experience with production multimodal systems spanning image, audio, and/or video. 
 
Deep expertise with diffusion and video generation techniques (e.g., ControlNet/IP-Adapter, temporal consistency methods, sampling and latency optimization). 
 
Experience with PEFT/QLoRA and post-training approaches such as DPO or related preference-based methods for small and mid-sized LLMs. 
 
Background in ASR/VAD/diarization, OCR, multimodal retrieval, or face recognition with fine-grained temporal alignment. 
 
Familiarity collaborating with infra/platform teams on model serving (e.g., batching strategies, quantization, observability) and translating requirements into reliable production deployments. 
 
Demonstrated ability to define metrics, build evaluation harnesses, and communicate results clearly to cross-functional partners. 
 
Track record of publications, patents, or open-source contributions in relevant areas of machine learning or multimodal modeling. 
 
Minimum Qualifications 
 
Master&rsquo;s degree in Computer Science, Electrical Engineering, or a related technical field, or equivalent practical experience. 
 
5+ years of hands-on industry experience building and shipping machine learning systems to production. 
 
Proven experience training and fine-tuning diffusion or other image/video generative models, including adapter-based methods such as LoRA. 
 
Proficiency in Python and at least one major deep learning framework such as PyTorch. 
 
Experience designing and operating ML pipelines for noisy or weakly labeled data, including offline evaluation and monitoring in production. 
 
Strong software engineering skills, including code quality, experimentation discipline, and debugging/profiling of model performance. 
 
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 $201,300 and $302,200, 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.

Staff Machine Learning Engineer, Apple Services Engineering

Are you excited to tackle some of the most ambitious technical challenges in Apple Intelligence? Be involved in collaborating closely with our machine learning researchers, engineers, and data scientists? 
 
Together, you will orchestrate groundbreaking research initiatives and develop transformative products designed to build a significant impact for billions of users worldwide! 
 
As part of Apple&rsquo;s AI and Machine Learning org, we encourage and create groundbreaking technology for large-scale ML systems, computer vision, natural language processing, and multi-modal understanding and generation. 
 
The Data and Machine Learning Innovation (DMLI) team is looking for Machine Learning Engineer to explore new methods, challenge existing metrics or protocols, and develop new insightful practices that will change how we understand data and overcome real-world ML challenges. 
 
Description 
 
As a Machine Learning (ML) Engineer, you will be entrusted with the critical role of innovating and applying state of the art research in ML to tackle complex data problems. 
 
The solutions you develop will significantly impact Apple Intelligence, future Apple products and the broader ML development ecosystem. 
 
You will work with a multidisciplinary team to actively participate in Apple Intelligence&rsquo;s data-model co-design and co-develop practice. 
 
Your responsibilities will extend to the design and development of a comprehensive data generation and curation framework for Apple Intelligence foundation models at Apple. 
 
You will also be responsible to build robust model evaluation pipelines, integral to the continuous improvement and assessment of Apple Intelligence foundation models. 
 
Furthermore, you will have the opportunity to showcase your groundbreaking research work by publishing and presenting at premier academic venues. 
 
&quot;,&quot;responsibilities&quot;:&quot;Develop and implement techniques for creating high-quality synthetic datasets across a variety of domains, including vision, text, and audio data. 
 
Innovate and experiment with new approaches for synthetic data generation to improve the diversity, realism, and representativeness of datasets. 
 
Collaborate with multi-functional teams to understand data requirements and ensure that synthetic datasets are optimized for training foundation models. 
 
Crafting and implementing semi-supervised, self-supervised representation learning techniques for growing the power of both limited labeled data and large-scale unlabeled data. 
 
Develop pipelines and tools to automate synthetic data generation for large-scale AI experiments. 
 
Stay updated with the latest research and industry trends in synthetic data generation, foundational model training, and large-scale data engineering. 
 
Preferred Qualifications 
 
3+ years of experience with developing and evaluating ML applications, and demonstrated experience in understanding and improving data quality. 
 
Strong publication record in relevant conferences (e.g. CVPR, ICCV, ECCV, NeurIPS, ICML, ICLR, etc). 
 
Strong problem-solving and communication skills. 
 
Experience of multimodal large language model or image/video generation model training is a plus. 
 
Ph.D/MS degree in Machine Learning, Natural Language Processing, Computer Vision, Data Science, Statistics or related areas. 
 
Minimum Qualifications 
 
Demonstrated expertise in computer vision, natural language processing, and machine learning with a passion for data-centric machine learning. 
 
Deep understanding in multi-modal foundation models. 
 
Staying on top of emerging trends in generative AI and multi-modal LLM. 
 
Strong programming skills and hands-on experience using the following languages or deep learning frameworks: Python, PyTorch, or Jax. 
 
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant . 
 
Pay &amp; Benefits 
 
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $171,600 and $302,200, 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>
 
 Summary
 
 
 
 Are you excited to tackle some of the most ambitious technical challenges in Apple Intelligence? Be involved in collaborating closely with our machine learning researchers, engineers, and data scientists? Together, you will orchestrate groundbreaking research initiatives and develop transformative products designed to build a significant impact for billions of users worldwide!
 
 
 As part of Apple's AI and Machine Learning org, we encourage and create groundbreaking technology for large-scale ML systems, computer vision, natural language processing, and multi-modal understanding and generation. The Data and Machine Learning Innovation (DMLI) team is looking for Machine Learning Engineer to explore new methods, challenge existing metrics or protocols, and develop new insightful practices that will change how we understand data and overcome real-world ML challenges.
 
 
 
 Description
 
 
 
 As a Machine Learning (ML) Engineer, you will be entrusted with the critical role of innovating and applying state of the art research in ML to tackle complex data problems. The solutions you develop will significantly impact Apple Intelligence, future Apple products and the broader ML development ecosystem.
 
 
 You will work with a multidisciplinary team to actively participate in Apple Intelligence&rsquo;s data-model co-design and co-develop practice. Your responsibilities will extend to the design and development of a comprehensive data generation and curation framework for Apple Intelligence foundation models at Apple. You will also be responsible to build robust model evaluation pipelines, integral to the continuous improvement and assessment of Apple Intelligence foundation models.
 
 
 Furthermore, you will have the opportunity to showcase your groundbreaking research work by publishing and presenting at premier academic venues.
 
 
 Your work may span a variety of directions, including but not limited to:
 
 
 Develop and implement techniques for creating high-quality synthetic datasets across a variety of domains, including vision, text, and audio data.
 
 
 Innovate and experiment with new approaches for synthetic data generation to improve the diversity, realism, and representativeness of datasets.
 
 
 Collaborate with multi-functional teams to understand data requirements and ensure that synthetic datasets are optimized for training foundation models.
 
 
 Crafting and implementing semi-supervised, self-supervised representation learning techniques for growing the power of both limited labeled data and large-scale unlabeled data.
 
 
 Develop pipelines and tools to automate synthetic data generation for large-scale AI experiments.
 
 
 Stay updated with the latest research and industry trends in synthetic data generation, foundational model training, and large-scale data engineering.
 
 
 
 Minimum Qualifications
 
 
 
 <ul>
 <li>
 Demonstrated expertise in computer vision, natural language processing, and machine learning with a passion for data-centric machine learning.
 </li>
 <li>
 Deep understanding in multi-modal foundation models.
 </li>
 <li>
 Staying on top of emerging trends in generative AI and multi-modal LLM.
 </li>
 <li>
 Strong programming skills and hands-on experience using the following languages or deep learning frameworks: Python, PyTorch, or Jax.
 
 
 </li>
 </ul>
 
 Preferred Qualifications
 
 
 
 <ul>
 <li>
 3+ years of experience with developing and evaluating ML applications, and demonstrated experience in understanding and improving data quality.
 </li>
 <li>
 Strong publication record in relevant conferences (e.g. CVPR, ICCV, ECCV, NeurIPS, ICML, ICLR, , etc)
 </li>
 <li>
 Strong problem-solving and communication skills.
 </li>
 <li>
 Ph.D/MS degree in Machine Learning, Natural Language Processing, Computer Vision, Data Science, Statistics or related areas
 
 
 </li>
 </ul>
 
 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&rsquo;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&rsquo;s Employee Stock Purchase Plan. You&rsquo;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 &mdash; including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits.
 
 
 Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
 
 
 Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant.
 
 
 Apple accepts applications to this posting on an ongoing basis.
 
 
</div>

AIML - Machine Learning Engineer, Data and ML Innovation

At Apple, we believe that technology should enrich people's lives in meaningful ways. Apple Services-including the App Store, Apple Music, Apple TV+, and Podcasts-connect millions of users worldwide to the content and experiences they love. Behind these services are sophisticated AI and machine learning systems that power personalized recommendations, intelligent search, and content discovery. The quality of these experiences depends fundamentally on the integrity of the data that fuels them. 
 
Join the Human-centered AI (HAI) organization within Apple Services Engineering as a Senior Applied Scientist on our Data Quality Operations team. This is your opportunity to shape the future of data quality at Apple, working at the intersection of cutting-edge machine learning, large language models, and rigorous scientific methodology. You'll be at the forefront of designing and implementing novel, scalable quality control solutions which ensure our AI-powered services meet Apple's exacting standards for a high-quality user experience. If you're passionate about applying scientific rigor to real-world problems, thrive on innovation, and want your work to impact hundreds of millions of users, this role offers an exceptional opportunity to make a lasting contribution to products people use every day. 
 
Description 
 
We are seeking a Senior Applied Scientist to lead the design and implementation of novel, scalable quality control solutions for Apple Services. In this role, you will develop AI or ML solutions for programatically generating gold standard datasets, create anomaly detection systems, and pioneer use of Large Language Models for automated quality control. You will work closely with cross-functional teams to ensure the data powering our AI/ML systems meets the highest standards of accuracy, consistency, and relevance. 
 
&quot;,&quot;responsibilities&quot;:&quot;Develop methodologies and systems to programatically generating gold standard datasets to measure and improve data quality across diverse content types. 
 
Build and validate LLM-based grading systems that align with human judgment for tasks including content classification, quality assessment, and metadata validation. 
 
Create and deploy anomaly detection systems to proactively identify data inconsistencies, biases, and errors across production pipelines. 
 
Collaborate with AI/ML engineering, product, and data science teams to identify quality challenges and integrate solutions into production workflows. 
 
Stay abreast of the latest advancements in machine learning, AI, data quality, and LLM research, applying relevant techniques to enhance our capabilities. 
 
Mentor and guide junior team members, fostering technical excellence and innovation in data quality operations. 
 
Communicate findings and recommendations clearly to technical and non-technical stakeholders, including senior leadership. 
 
Preferred Qualifications 
 
PhD in Computer Science, Machine Learning, Statistics, Applied Mathematics, NLP or a related quantitative field with 3+ years of relevant industry experience, 
 
Experience with data labeling operations, annotation quality frameworks, or human-in-the-loop systems. 
 
Familiarity with prompt optimization frameworks or automated prompt engineering. 
 
Experience in natural language processing (NLP) or natural language understanding (NLU). 
 
Experience with MLOps practices and tools for deploying, monitoring, and managing ML models in production. 
 
Familiarity with cloud platforms (e.g., AWS, GCP, Azure) or large-scale distributed infrastructure systems. 
 
Prior experience contributing to open-source projects or publishing research in relevant academic conferences or journals. 
 
Minimum Qualifications 
 
3+ years of industry experience in an Applied Scientist, Machine Learning Engineer, or Data Scientist role with focus on data quality, evaluation, or related areas. 
 
Proven experience designing, building, and deploying scalable data quality or evaluation systems in production environments. 
 
Strong hands-on experience with Large Language Models (LLMs) including prompt engineering, fine-tuning, and applications such as grading, validation, or classification. 
 
Proficiency in Python, data science libraries (pandas, NumPy, scikit-learn, PyTorch, TensorFlow), SQL, and distributed computing environments (Spark, Hadoop). 
 
MS in Computer Science, Machine Learning, Statistics, Applied Mathematics, NLP or a related quantitative field with 3+ years of relevant industry experience, OR BS degree in a related quantitative field with 8+ years of relevant industry 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 $171,600 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.

Sr Applied Scientist, AI/ML Evaluation Quality, Apple Services Engineering

Join Apple&rsquo;s Information Security Machine Learning (ISML) team, where we are redefining cybersecurity through data-driven intelligence. Our mission is to transform traditional reactive security measures into autonomous systems that proactively detect and defend against threats. We achieve this through cutting-edge research, applied science, and robust infrastructure development. We are seeking a highly motivated and talented Machine Learning Engineer to join our dynamic and growing team. You will play a pivotal role in designing, developing, and deploying machine learning models that power our advanced security products and services. This is an incredible opportunity to make a real world impact by building intelligent systems that detect and prevent advanced threats, enhance critical security processes, and protect Apple and our customers. 
 
Description 
 
The Security ML Engineer will bring their expertise in machine learning to the problems and opportunities facing Information Security at Apple. You will contribute to the Autonomous Security program by developing production ready AI/ML systems using Apple&rsquo;s internal platforms, cloud services, and local compute environments. 
 
You will translate research to design, building and deploying machine learning models for security use cases, leveraging generative AI, statistical modeling, reinforcement learning, and data science to address complex security challenges. You will collaborate with cross-functional teams including security teams, software engineers, and researchers to prototype and scale AI/ML driven security solutions. You will own end-to-end ML workflows: data exploration, model development, evaluation metrics design, deployment, and monitoring. 
 
Preferred Qualifications 
 
Ph.D. in a technical field such as Computer Science, Engineering, Statistics, or related disciplines. 
 
In-depth knowledge of ML algorithms, including supervised/unsupervised learning, deep learning (CNNs, RNNs, LSTMs), and large language models. 
 
Industry experience in deploying ML and generative AI solutions in cybersecurity contexts. 
 
Familiarity with cloud platforms (e.g., AWS, GCP) and their security offerings is a plus. 
 
Experience with large scale data processing and analysis using tools such as Apache Spark. 
 
Experience working in a key security process, such as Incident Response, Threat Intelligence, or Vulnerability Management. 
 
Experience with specific security tools and technologies (e.g., SIEM, IDS/IPS, endpoint security solutions). 
 
Contributions to open-source security or machine learning projects. 
 
Publications or talks at top-tier ML or security conferences. 
 
Additional proficiency in C++ or Swift is a plus 
 
Minimum Qualifications 
 
BSc or Masters degree in Machine Learning, Data Science, Computer Science, Information Security, Mathematics, Statistics, or related field. 
 
Strong programming skills in Python and Scala; experience with ML libraries such as TensorFlow, PyTorch, HuggingFace, and Scikit-learn. 
 
Hands-on experience with full ML model lifecycle: from experimentation to deployment and monitoring. 
 
Solid grasp of security fundamentals including network security, incident response, threat modeling, and vulnerability management. 
 
Excellent written and verbal communication skills, with the ability to present technical concepts clearly to varied audiences. 
 
Familiarity with CI/CD workflows and ML pipelines . 
 
Experience operating, and scaling production services in cloud native environments. 
 
Experience deploying models on CUDA devices using tools like TensorFlow or Torch. 
 
Proven experience building generative AI applications for real-world use cases. 
 
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, Information Security

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