aiml - machine learning engineer, data and ml innovation

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ai/ml engineer: system rf data ecosystem Jobs in Cupertino

ai/ml engineer: system rf data ecosystem

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

aiml - machine learning engineer, mlr Jobs in Cupertino

aiml - machine learning engineer, mlr

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

aiml - sr applied ai scientist - genai model autograding, evaluation Jobs in Cupertino

machine learning data scientist predictive semantics team apple ads

Apple

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 
 
The role requires experience in areas such as predictive modeling (classification and regression), optimization, industrial engineering, demand forecasting, and time-series forecasting. The ideal candidate will have demonstrated capability to deploy data science and machine learning models with large datasets in an industry setting. Deep understanding and ability to compare predictive models, evaluate their strengths and weaknesses in a particular context, and interpret and explain model results to a broad group of technical and non-technical stakeholders are also a plus. Competitive candidates will also have experience working closely with data engineers to build efficient, scalable solutions. We are looking for a thoughtful and creative data scientist to join a team that creatively adapts state-of-the art analytical techniques to real-world business problems with an approach focused on rapid development, evaluation, and iterative improvement. Continuous learning is part of the job, both as it relates to technical skills and within the content and format of advertising domain&quot;,&quot;responsibilities&quot;:&quot;4+ years of recent experience in a data science role. 
 
Bachelor's in computer science, mathematics, or another quantitative field 
 
Command over Python and SQL. 
 
Comfort with cloud technologies such as AWS and Snowflake. 
 
Experience with Big Data tools such as Hadoop, Spark and PySpark. 
 
Experience in quantitative analysis including regression, classification, linear optimization, supply chain analytics, and time-series analyses. 
 
Ability to communicate the results of analyses in a clear and effective manner with product and leadership teams to influence the overall strategy of the product. 
 
Ability to partner with engineering, meet the data needs of the business, find creative analytical solutions, and develop initial prototypes to address business problems. 
 
Experience with end-to-end implementation of a model prototype specifically training, processing, feature engineering, evaluating model outputs, and putting models into production. 
 
Preferred Qualifications 
 
Masters degree or Ph.D. in a quantitative discipline. 
 
Experience in the digital advertising industry or a related field and/or experience with demand forecasting 
 
Willingness to learn, both technically and in the domain of the data. 
 
Familiarity with packages like numpy, pandas, scikit-learn, and prophet 
 
Familiarity with job orchestration frameworks like git, Airflow, CI/CD, Kubernetes, Docker, Jenkins. 
 
Experience and/or interest in deep learning, LLMs, and Natural Language Processing. 
 
Minimum Qualifications 
 
5+ years of experience in Business Analytics, Data Science, or a related analytical role 
 
Strong data analysis skills, including the ability to conduct deep dives using statistical methods and data science techniques 
 
Exceptional communication skills, with the ability to communicate complex analyses clearly to executive and technical audiences 
 
Demonstrated ability to collaborate with cross-functional partners such as Product, Sales, and Marketing to design experiments and analyses that inform business decisions 
 
Proficiency in SQL and data visualization, with a strong eye for design and clarity 
 
Strong programming skills in Python, with experience using libraries such as Pandas, SciPy, and scikit-learn 
 
Comfortable querying and analyzing large datasets using tools such as SQL, Snowflake, or similar analytical data platforms 
 
Bachelor&rsquo;s degree in a related field, or equivalent 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 $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 Data Scientist - Predictive Semantics Team, Apple Ads

<div>Our mission is to personalize the user experience on Apple devices based on where you go, when, and what those places mean to you. You're experiencing our work whenever you see a suggested location in Maps or Calendar, or browse your Memories in Photos or Journal. We're working for you whenever your phone engages Do Not Disturb While Driving or remembers where you parked. 
 
We're the Location Context team, and we build the location intelligence backbone powering Maps Visited Places, Siri location suggestions, and predictive features across the OS. We're looking for engineers who love solving hard problems at the intersection of location state estimation, on-device machine learning, and privacy-preserving systems. 
 
Are you excited by any of these challenges? 
 
<ul><li>Building location state estimators that fuse GPS, WiFi, IMU, and altimeter data to understand not just where users are, but what floor of a building they're on</li></ul> 
<ul><li>Designing ML models to infer the semantics of a place and forecast where the device will go next, entirely on-device with strict power and memory budgets</li></ul> 
<ul><li>Developing clustering algorithms and data pipelines that process billions of location events while preserving user privacy</li></ul> 
<ul><li>Optimizing system performance at massive scale-where a 1% edge case impacts 10 million devices and a power regression of 0.1% matters</li></ul> 
<ul><li>Collaborating with Maps, Siri, Photos, HomeKit, Journal, and Safety teams to power features that require deep contextual understanding</li></ul> 
If this sounds like you, read on. 
 
Description 
 
In this role, you'll develop the next frontier of location intelligence, in partnership with teams across sensing, Siri, Maps, and system frameworks. You'll work on problems from research through production deployment: 
 
Design and implement location state estimation algorithms that fuse multi-modal sensor data (GPS, WiFi positioning, accelerometer, altimeter, barometer) to build a rich understanding of user context and mobility patterns 
 
Develop on-device machine learning models for place inference, route prediction, and behavioral forecasting that operate within strict power and memory constraints 
 
Build data processing pipelines that aggregate, filter, and cluster real-world sensor data on mobile devices, balancing intelligence with resource constraints 
 
Implement sophisticated algorithms for background location awareness and semantic understanding - then integrate them into production code running on hundreds of millions of devices 
 
Collect and analyze real-world datasets to train models, validate performance, and iterate on algorithm design 
 
Test rigorously. Dogfood your work. Collect metrics across diverse user populations and edge cases. An issue that affects 1% of a billion devices is a big issue. 
 
Optimize for the full system: CPU, memory, power consumption, and radio usage. Our software needs to provide a high level of intelligence while sipping battery-this is one of the most exciting engineering challenges in mobile computing. 
 
A dedication to users' privacy and security is core to how Apple does business. We want their devices to exhibit the high level of intelligence and proactivity that can only come from deep contextual understanding. We don't want their sensitive data coming back to Apple or being exposed to third parties. Other companies solve similar problems in very different ways. Our way is more work. We believe it's worth it. 
 
&quot;,&quot;responsibilities&quot;:&quot;Conceptualize, explore, and define new inferential and predictive location- and motion-based capabilities for Apple's platforms 
 
Design and implement location state estimation algorithms, sensor fusion techniques, and ML models for on-device inference 
 
Develop clustering and pattern recognition algorithms to identify significant locations, routes, and behavioral patterns from noisy sensor data 
 
Build and optimize data processing pipelines that operate within strict power and memory budgets on mobile hardware 
 
Collect, curate, and analyze real-world datasets of varying size and complexity to validate algorithm performance 
 
Integrate algorithms into production code (Objective-C, Swift, C++), working within daemon and framework architectures 
 
Profile and optimize system performance: measure CPU, memory footprint, power consumption, and latency; iterate to improve 
 
Collaborate across teams (Maps, Siri, Photos, Health, Safety) to understand requirements and deliver capabilities that enable compelling user experiences 
 
Write robust, maintainable code. Test thoroughly. Address edge cases. Build systems that scale to billions of devices. 
 
Preferred Qualifications 
 
Deep expertise in location technologies: GPS/GNSS positioning, WiFi-based localization, indoor positioning, sensor fusion for state estimation, or IMU-based dead reckoning. If you've built location estimators that fuse multiple sensor modalities, we especially want to hear from you. 
 
Experience with machine learning for time-series data, spatial data, or behavioral prediction. On-device ML experience (model size optimization, quantization, power-efficient inference) is a strong plus. 
 
Background in signal processing, Kalman filtering, particle filters, or other probabilistic state estimation techniques. 
 
Experience with clustering algorithms (DBSCAN, hierarchical clustering, etc.) and unsupervised learning applied to spatial or temporal data. 
 
Track record of shipping production systems that operate at scale under resource constraints (mobile, embedded, or edge computing environments). 
 
Strong collaboration skills and ability to work effectively across teams with diverse expertise. At Apple, you'll partner closely with teams in sensing, connectivity, privacy, and application frameworks. You'll need to communicate clearly, plan collaboratively, and execute flexibly. 
 
Experience with performance profiling tools (Instruments, dtrace, etc.) and systematic optimization of CPU, memory, and power usage. 
 
Experience with large-scale data analysis for offline algorithm development, model validation, and performance evaluation across diverse user populations. 
 
Minimum Qualifications 
 
5+ years experience developing commercial software, preferably systems-level or embedded software running on resource-constrained devices 
 
Strong programming skills in C, C++, Objective-C, or Swift, with solid foundation in algorithms, data structures, and computational complexity 
 
Working knowledge of statistics and probability, including comfort with histograms, probability distributions, Bayesian inference, and hypothesis testing 
 
Experience evaluating and optimizing system performance: memory footprint, CPU usage, power consumption, and I/O 
 
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.</div>

Software Development Engineer - Location Technologies

At Apple, we believe in the power of technology to enrich people's lives. Everything we build is designed to empower people, including our advertising platform. We deliver ads in a way that benefits both consumers and advertisers - helping people discover content, supporting creators, and protecting and respecting everyone&rsquo;s privacy. 
 
Our technology makes advertising possible on the App Store, Apple News, Stocks, and Apple TV. We help developers and marketers of all sizes drive app discovery across the App Store. Our display ads on Apple News and Stocks let advertisers promote their products alongside trusted content in a brand-safe environment, while supporting publishers and journalists. Sponsorship integrations and experiences in live sports on Apple TV help advertisers connect with captivated audiences. Everything we do is with the unwavering commitment to privacy you expect from Apple. Because when advertising is done right, it benefits everyone. 
 
Description 
 
Our platforms are highly performant, deployed at scale, and set new standards for enabling effective advertising while protecting user privacy. The Ad Platforms Data Insights team is seeking a Data Scientist to join in developing the next generation of analytical solutions in collaboration with Engineering, Product, Sales, Marketing, and Finance. In this role you will work as a key member of a data-centric team to drive the exploration, analysis, development, execution, and measurement solutions that are essential to running and growing the ads marketplace. Responsibilities include turning the huge amounts of data generated by user searches, app content, and App Store context into business insights that improve the customer experience for the end-user as well as drive discovery and efficiency for app developers. 
 
This role requires both a broad knowledge of statistics and creativity to invent and customize when vital. You'll dig in and get into the details. The theory behind the techniques are just the beginning. You'll be working on projects where practical applications of these approaches get applied in real-world scenarios. Successful analytics teams involve data scientists and data engineers working hand in hand to build insightful and efficient solutions. In your role, you will be a key player in a multi-functional team that delivers insights that have direct and measurable impact. We're looking for an inquisitive, collaborative, and passionate person to join this amazing team.&quot;,&quot;responsibilities&quot;:&quot;Support Marketplace Product, Engineering, and the Executive Team with analyses, and data products to improve product performance, deepen customer insight and deliver business impact. 
 
Empower the product and algorithm engineering team with insights to advise and fulfill their strategic objectives and goals. 
 
Quantify the impact of marketplace initiatives on advertiser impact, and business performance. 
 
Design experiments that help define opportunities for pricing, matching, and prediction models leading to improved marketplace performance, and positive advertiser impact. 
 
Monitor usage metrics and provide business-based explanations for large scale trends and patterns in advertiser lifecycle behavior. 
 
Develop reusable models and data products working closely with Data Engineering team to ensure scalability of models and products in production. 
 
Lead business analytics projects through all phases, including defining investigations, exploring data, conducting analysis, interpreting, and presenting results for customers 
 
Preferred Qualifications 
 
4+ years of recent experience in a data science role. 
 
Experience in the mobile advertising industry or related field. 
 
Familiarity with job orchestration frameworks such as Airflow. 
 
Demonstrated ability to build visualizations, dashboards and enable broader consumption of insights and tools for investigations. 
 
Post-Bachelor's degree in Data Science, Applied Mathematics, Statistics, Computer Science or relevant field/experience 
 
Minimum Qualifications 
 
2+ years of recent experience in a data science role. 
 
Programming skills in Python and SQL, and familiarity with machine learning, such as scikit-learn, xgboost, PyTorch, SciPy is necessary. 
 
Familiar with statistical analysis methods, most notably regression analysis, causal inference, statistical learning and A/B and quasi-experimentation methods. 
 
Demonstrated experience in applying statistics and machine learning to generate clear actionable insights. 
 
Comfortable with a variety of data stores such as Hadoop, and Snowflake, familiar with distributed analytics engines such as Spark/PySpark. 
 
Possess exceptional communication skills to communicate analyses in a clear and effective manner to technical audience and executive leadership. 
 
Demonstrated ability to partner with engineering, meet the data needs of the business, finding creative analytical solutions and develop initial prototypes to address messy business problems. 
 
Proven ability to operate comfortably and optimally in a fast-paced and constantly evolving environment. 
 
Bachelor's degree in Data Science, Applied Mathematics, Statistics, Computer Science or relevant field/experience 
 
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant . 
 
Pay &amp; Benefits 
 
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $147,400 and $272,100, and your base pay will depend on your skills, qualifications, experience, and location. 
 
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits. 
 
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

Senior ML Data Scientist - Marketplace, Apple Ads

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! 
 
You'll have the opportunity to develop models that improve our platform across the board, write production code to generate recommendations, work closely with business partners to help drive the development of new products as well as perform large scale and complex experiments to understand their effects. You'll drive strategic outcomes through substantial innovation in multiple fields by leading the development and application of advanced techniques and algorithms to improve our ad network. 
 
You've, or will develop a deep understanding of the ad network behavior, and will work with product management and business leadership to prioritize an innovation roadmap across multiple technical domains. You'll lead the conception, development, and delivery of state of the art capabilities that differentiate our products and are core to our business. You should have experience developing and implementing machine learning algorithms, ideally within the ads space. You'll have an excellent understanding of scalable architectures and thrive working in Agile environments. The ability to be a good team player under tight deadline constraints is key to success. 
 
Description 
 
Matching at Ads is a critical component of our Ads funnel and responsible for ensuring that we are retrieving relevant and engaging Ads for our users. We are building the next generation of our retrieval systems to sustain the growth of the business for the future. We are looking for a Machine Learning Engineer that will develop the algorithms for our retrieval system. 
 
In this role you will drive step-change improvements in our outcomes, impact our platform revenue and quality of our ads, and formulate approaches to greenfield product opportunities. You will own end-to-end the ideation, development, testing and productization of these algorithms. You will work with complex problems in the ads retrieval space, provide solution that adhere to Apple&rsquo;s privacy principles, review and contribute to state of the art in research, work with a variety of cross functional teams to ensure the feasibility and robustness of delivering new capabilities. This role will work closely with organizational partners and be expected to present findings across the organization. 
 
Preferred Qualifications 
 
7+ years of experience building machine learning capabilities across many different product areas at scale. 
 
PhD, or equivalent experience, in NLP, Machine Learning, Deep Learning, Large Language Model, Reinforcement Learning or related field with experience building production systems or have equivalent experience working with large data science / machine learning projects in industry. 
 
Minimum Qualifications 
 
4+ years of experience building machine learning capabilities across many different product areas at scale. 
 
Proven experience in NLP, information retrieval and search. 
 
Ability to apply and implement research concepts, ultimately in production quality code. 
 
Experience defining clear, testable research hypotheses, including intended impact on the business. 
 
Deep understanding of design of experiments, online experimentation approaches, preferably at scale. 
 
Experience contributing and/or reviewing research for top conferences and publications. 
 
Master's, or equivalent experience, in NLP, Machine Learning, Statistics, Forecasting, Optimization, Reinforcement Learning or related field with experience building production systems or have equivalent experience working with large data science / machine learning projects in industry. 
 
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.

Senior Machine Learning Engineer - Matching, Apple Ads

Services at Apple help hundreds of millions of customers get the most out of the devices they love through amazing apps, award-winning shows and movies, immersive music in spatial audio, world-class workouts and meditations, super fun games and more! The Services Data Science &amp; Analytics organization is passionate about developing discerning insights and AIML solutions to help continually improve these services and accelerate growth while maintaining a strong dedication to customer privacy. 
 
We are currently seeking an experienced and passionate Applied ML Science Manager to lead a dynamic team, whose goal is to provide innovative products at the intersection of causal inference, statistics, and machine learning to help drive key business decisions and optimize marketing channels, via observational testing frameworks, counterfactual modeling, and lifetime value estimation. As a key member of our diverse organization, you'll have the rare and rewarding opportunity to work with datasets of unique magnitude, richness, and dedication to privacy that will frequently require novel approaches. You'll work alongside partners across Business, Marketing, Product, Finance, and Engineering daily to deliver material customer and business value. 
 
Description 
 
As an Applied ML Science Manager, you will have the responsibility of leading a highly talented team of scientists and engineers dedicated to pushing the boundaries of how Causal Inference and AIML can be leveraged to better serve our customers, focusing on Services such as Apple TV, Apple Music, Apple One, and the App Store. You will be at the forefront of designing, developing, and deploying cutting-edge Causal Inference solutions, that directly impact our products and provide a granular understanding of key business initiatives and marketing effectiveness. You will also be instrumental in defining the technical vision, strategy, and execution roadmap for our AIML initiatives, ensuring that we deliver high-quality, scalable, and impactful models that solve complex customer acquisition and engagement challenges. Beyond technical leadership, you will be a key driver in fostering a vibrant culture of innovation, continuous learning, and collaborative problem-solving within your team.&quot;,&quot;responsibilities&quot;:&quot;Lead, mentor, and grow a high-performing team of Applied Scientists and Machine Learning Engineers, fostering a culture of innovation and collaboration 
 
Drive team goals, priorities, and career development, including recruitment and onboarding 
 
Oversee the technical strategy, design, and full lifecycle of scalable, robust Causal Inference and Machine Learning products 
 
Manage timelines, resources, and deliverables, ensuring projects are completed on time, within scope, and communicated to stakeholder teams 
 
Collaborate with product managers, data scientists, and other engineering teams to translate business requirements into technical specifications and deliver impactful, practical solutions, increasing internal adoption of causal inference approaches and democratizing data 
 
Stay abreast of the latest advancements in causal inference and AIML research, evaluating and integrating new frameworks where appropriate 
 
Champion best practices in software engineering, MLOps, code quality, testing, documentation, and ensure compliance with data privacy and security 
 
Preferred Qualifications 
 
PhD in related field 
 
Hands-on experience leveraging Generative AI to improve productivity and generate new insights 
 
Curious business attitude with an ability to condense complex concepts and models into clear and concise takeaways that drive action 
 
Minimum Qualifications 
 
Master&rsquo;s degree in Statistics, Economics, Mathematics, Machine Learning, Computer Science, Engineering, or a related technical field 
 
3+ years of experience in a leadership or management role, leading Applied Scientists, Machine Learning Engineers and Data Scientists 
 
5+ years of experience as an Applied Scientist, Machine Learning, or Data Scientist role 
 
Familiarity with a brand range of quasi-experimental Causal Inference techniques such as diff-in-diff, synthetic control method, panel analysis, regression discontinuity design, interrupted time series, and propensity score matching 
 
Working knowledge of Marketing Mix models and validation through Matched Market testing 
 
Practical expertise leveraging Customer Lifetime Value models to drive business decision-making 
 
Solid understanding of AIML technologies including Generative AI 
 
Proven track record of successfully delivering complex projects from start to finish 
 
Proficiency in programming languages such as Python, R, SQL, Java, or C++ 
 
Experience with cloud platforms, Spark, Docker, and MLOps tools and best practices 
 
Excellent communication, collaboration, and presentation skills with meticulous attention to detail 
 
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 $198,300 and $342,800, 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 Science Manager

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 
 
Apple&rsquo;s Ads Signals Intelligence team is seeking a hands-on and experienced Machine Learning Engineer to develop the next generation of ML-driven signal platforms that power retrieval, prediction, and relevance across Apple&rsquo;s advertising ecosystem-including the App Store and Apple News. This role focuses on building content understanding systems and large-scale infrastructure capable of delivering near real-time signal updates, enabling smarter, privacy-aware decision-making throughout the ad delivery stack. 
 
This role focuses on developing rich semantic signals from a variety of sources-including queries, creatives, metadata, and user interactions-to support scalable ad retrieval, creative ranking, and marketplace optimization. You'll work at the forefront of LLM fine-tuning, knowledge graph construction, semantic search, and multimodal representation learning to extract structured intelligence from unstructured data. 
 
While ad tech knowledge is a strong bonus, the core of the role is building high-quality, privacy-centric signals that fuel some of Apple&rsquo;s most advanced machine learning systems. 
 
As part of the Ads Signals Intelligence team, you&rsquo;ll be shaping the foundation of Apple&rsquo;s ad ranking and relevance systems through world-class signal understanding. You&rsquo;ll work on problems at the cutting edge of retrieval, multimodal learning, LLMs, and content intelligence-while contributing to Apple&rsquo;s mission to deliver high-performing, privacy-first advertising experiences at scale.&quot;,&quot;responsibilities&quot;:&quot;Design, implement, and scale ML systems that extract high-value semantic signals from structured and unstructured content 
 
Contribute to retrieval and ranking pipelines using techniques in query understanding, semantic embedding, and dense/sparse indexing 
 
Fine-tune and apply Large Language Models (LLMs) for NLP tasks like content labeling, rewriting, and semantic similarity 
 
Construct and utilize knowledge graphs and entity linking systems for enriching creative and query signals 
 
Work with multimodal data (e.g., combining text, image, and metadata signals) to build robust, cross-domain signal representations 
 
Build core components for a content understanding platform, such as entity extraction, topic modeling, creative summarization, and taxonomy generation 
 
Own experimentation, offline evaluation, and online validation of signal pipelines at massive scale 
 
Collaborate across engineering, infra, and product teams to productionize systems while meeting Apple&rsquo;s high standards for reliability and privacy 
 
Preferred Qualifications 
 
7+ years of experience in machine learning or applied research, with a focus on retrieval, ranking, NLP, or content understanding 
 
MS or PhD in Computer Science, Machine Learning, Information Retrieval, NLP, or a related field. 
 
Minimum Qualifications 
 
4+ years of experience in machine learning or applied research, with a focus on retrieval, ranking, NLP, or content understanding 
 
Deep understanding of information retrieval, semantic search, and query-document matching 
 
Strong hands-on experience with LLM fine-tuning, knowledge graph construction, and entity-centric modeling 
 
Experience working with multimodal models, including text, vision, metadata, or audio-based representations 
 
Proficiency in Python, and experience with one or more of ML frameworks like PyTorch, TensorFlow 
 
Background in statistical modeling, optimization, and ML theory 
 
Exposure to ad tech domains such as auction modeling, targeting, attribution, or creative optimization is a plus 
 
Demonstrated ability to deliver high-impact ML solutions in production environments 
 
Bachelor's in Computer Science, Machine Learning, Information Retrieval, NLP, or a related field. 
 
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.

Staff Machine Learning Engineer - Ads Signals Intelligence & Information Retrieval

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 
 
Apple&rsquo;s Ads Signals Intelligence team is seeking a hands-on and experienced Machine Learning Engineer to develop the next generation of ML-driven signal platforms that power retrieval, prediction, and relevance across Apple&rsquo;s advertising ecosystem-including the App Store and Apple News. 
 
This role focuses on building content understanding systems and large-scale infrastructure capable of delivering near real-time signal updates, enabling smarter, privacy-aware decision-making throughout the ad delivery stack. This role focuses on developing rich semantic signals from a variety of sources-including queries, creatives, metadata, and user interactions-to support scalable ad retrieval, creative ranking, and marketplace optimization. 
 
You'll work at the forefront of LLM fine-tuning, knowledge graph construction, semantic search, and multimodal representation learning to extract structured intelligence from unstructured data. While ad tech knowledge is a strong bonus, the core of the role is building high-quality, privacy-centric signals that fuel some of Apple&rsquo;s most advanced machine learning systems. 
 
As part of the Ads Signals Intelligence team, you&rsquo;ll be shaping the foundation of Apple&rsquo;s ad ranking and relevance systems through world-class signal understanding. You&rsquo;ll work on problems at the cutting edge of retrieval, multimodal learning, LLMs, and content intelligence-while contributing to Apple&rsquo;s mission to deliver high-performing, privacy-first advertising experiences at scale.&quot;,&quot;responsibilities&quot;:&quot;Design, implement, and scale ML systems that extract high-value semantic signals from structured and unstructured content 
 
Contribute to retrieval and ranking pipelines using techniques in query understanding, semantic embedding, and dense/sparse indexing 
 
Fine-tune and apply Large Language Models (LLMs) for NLP tasks like content labeling, rewriting, and semantic similarity 
 
Construct and utilize knowledge graphs and entity linking systems for enriching creative and query signals 
 
Work with multimodal data (e.g., combining text, image, and metadata signals) to build robust, cross-domain signal representations 
 
Build core components for a content understanding platform, such as entity extraction, topic modeling, creative summarization, and taxonomy generation 
 
Own experimentation, offline evaluation, and online validation of signal pipelines at massive scale 
 
Collaborate across engineering, infra, and product teams to productionize systems while meeting Apple&rsquo;s high standards for reliability and privacy 
 
Preferred Qualifications 
 
7+ years of experience in machine learning or applied research, with a focus on retrieval, ranking, NLP, or content understanding 
 
MS or PhD in Computer Science, Machine Learning, Information Retrieval, NLP, or a related field. 
 
Minimum Qualifications 
 
4+ years of experience in machine learning or applied research, with a focus on retrieval, ranking, NLP, or content understanding 
 
Deep understanding of information retrieval, semantic search, and query-document matching 
 
Strong hands-on experience with LLM fine-tuning, knowledge graph construction, and entity-centric modeling 
 
Experience working with multimodal models, including text, vision, metadata, or audio-based representations 
 
Proficiency in Python, and experience with one or more of ML frameworks like PyTorch, TensorFlow 
 
Background in statistical modeling, optimization, and ML theory 
 
Exposure to ad tech domains such as auction modeling, targeting, attribution, or creative optimization is a plus 
 
Demonstrated ability to deliver high-impact ML solutions in production environments 
 
Bachelor's in Computer Science, Machine Learning, Information Retrieval, NLP, or a related field. 
 
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 Machine Learning Engineer - Ads Signals Intelligence and Information Retrieval

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