aiml - applied ml engineer, responsible ai

aiml - machine learning engineer, data and ml innovation

administrative assistant - beats, home, accessory, and ecosystem

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

ai/ml engineer: system rf data ecosystem

aiml - ai software engineer, evaluation Jobs in Cupertino

aiml - ai software engineer, evaluation

aiml - applied ml engineer, responsible ai Jobs in Cupertino

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 engineer mlr

Apple

As part of Apple&rsquo;s Machine Learning Research organization, we do world-class scientific research and build the technologies that will power future products at Apple. The techniques and tools we create will impact ML solutions across Apple, which in turn power most of the features we deliver to billions of consumers worldwide. We are looking for highly motivated, result-oriented engineers with a strong background in system engineering and software development to join our team. In this position you will work with researchers and software engineers across the Machine Learning Research group to build scalable, distributed training and research pipelines. 
 
Description 
 
Work with researchers and software engineers on the MLX team to build high performance and scalable software addressing novel ML research algorithms - Apply solid software engineering skills, leverage experience to deal with the unexpected, explore research software solutions and pave the way to future Machine Learning toolboxes. Be part of a small team dedicated to advancing ML algorithms and techniques on Apple silicon - Is this you? If so we'd love to hear from you. 
 
Preferred Qualifications 
 
3+ years in C++ and Python programming 
 
3+ Expert in GPU programming. 
 
Experience with Swift programming is a plus 
 
Experience and passion to circumvent unexpected roadblocks 
 
Past research experience is a plus 
 
Minimum Qualifications 
 
2 years in C++ and Python numerical computing 
 
2 years in GPU programming 
 
Experience with open-source projects and collaborative software development. 
 
Experience with Machine Learning algorithms. 
 
Excellent communication skills. 
 
B.S., M.S. or PhD in Computer Science with a strong mathematical background 
 
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.

AIML - Machine Learning Engineer, MLR

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

Imagine what you could do here. At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Do you love thinking analytically? Are you passionate about solving complex business problems in a fast-paced environment? The AIML Data Operations group engages with teams across Apple&rsquo;s ecosystem with the ultimate goal of delivering high-quality annotated data in support of unreleased products and ground breaking AI technology. 
 
We are currently seeking an experienced and influential Data Science Leader to grow the AIML Data Operations Annotations Analytics team and function. This position will lead a team of data engineers and scientists to establish top-line health metrics, identify key growth drivers, and recommend operational and business optimizations through scalable, responsive, and interpretable research and analyses. 
 
Description 
 
The ideal candidate for this role is an experienced manager with deep expertise in analytics and experimentation, excels at building strong cross-functional relationships to drive data-informed decisions across the company, and is skilled at leading teams to surface and communicate key data insights that improve performance and customer experience at a global scale.&quot;,&quot;responsibilities&quot;:&quot;Establish a center of excellence for Data Operations Data Science team by uncovering business-actionable insights in collaboration across our customer groups as well as the Operations team. 
 
Oversee large complex projects from conception to completion, develop roadmaps and requirements, identify risks and develop contingency plans, evaluate impact, and regularly communicate status to executives. 
 
Establish, enhance, and socialize key operational metrics that accurately represent the business state of health. 
 
Lead proactive analyses identifying key drivers of metrics, and make recommendations that optimize performance. 
 
Develop reporting measures to expand the portfolio of self-service dashboards and reports to inform, enable, and empower relevant stakeholders. 
 
Draft schema and instrumentation requirements to enrich operational datasets for new projects, etc. 
 
Identify key factors that lead to improving productivity and quality. 
 
Build a holistic view of analyst behaviors across the various platforms, and identify synergies that drive a more positive analyst experience and engagement. 
 
Develop, recruit, and train a diverse team of high-performing data engineers and scientists focused on uncovering insights from large-scale data across all aspects of the operation. 
 
Preferred Qualifications 
 
Masters degree or PhD in Computer Science, Statistics, Mathematics, Engineering, Economics or related field. 
 
Experience with the deployment of Large Language Models / Generative AI in service of efficiency in operations 
 
Excellent communication and presentation skills with meticulous attention to detail and the ability to collaborate effectively between business and analytic teams at multiple levels of the organization 
 
Experience in managing data science or analytics teams in AI &amp; ML annotations and collections areas. 
 
Passion for AIML and Operations, with a consistent track record of operational results. 
 
Minimum Qualifications 
 
Bachelors degree in Computer Science, Statistics, Mathematics, Engineering, Economics or related field. 
 
4+ years of experience in managing data science, analytics, or data operations teams 
 
4+ years of experience in data science with proven skills in developing meaningful and concise analytic objectives from general business goals 
 
Tested capabilities and comfort in scalable schema designs, relational database and big data technologies, ETL, code management, and query performance optimization 
 
Mastery in SQL-based languages, and proficiency in at least one large-scale data languages 
 
Strong hands-on experience interpretable with machine learning models and sophisticated analytic solutions using scripting tools such as Python or R 
 
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 $176,600 and $313,500, 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.

Data Science Leader, AIML Data Operations

Imagine what you could do here. At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Do you love thinking analytically? Are you passionate about solving complex business problems in a fast-paced environment? The AIML Data Operations group engages with teams across Apple&rsquo;s ecosystem with the ultimate goal of delivering high-quality annotated data in support of unreleased products and ground breaking AI technology. Within the Data Operations organization, the Capacity Planning &amp; Analytics team provides forecasting, capacity planning and optimization, data products, metrics reporting, modeling &amp; experimentation, and ad hoc analyses. 
 
We are seeking a highly motivated Senior Data Scientist to lead analysis into annotation project trends to uncover patterns in annotator performance, task complexity, and data characteristics to help optimize task design. You will translate behavioral insights and empirical findings into optimized project structures and workflows, and power capacity planning &amp; optimization with quantitative rigor-all to ensure we consistently launch projects that are smarter in design, faster in execution, and uncompromising in quality. You will partner closely with Data Ops Client Engagement, Human Factors engineering and annotation customers to collaborate on the most effective methods. 
 
Description 
 
The ideal candidate for this role is an experienced data scientist with deep expertise in analytics and experimentation, who excels at building strong cross-functional relationships to drive data-informed decisions across the company, and is skilled at partnering with operations and engineering teams to surface and communicate key data insights that improve performance and customer experience at a global scale.&quot;,&quot;responsibilities&quot;:&quot;As a Data Operations Capacity Planning &amp; Analytics Data Scientist, you will: 
 
Analyze trends across projects to identify patterns in annotator performance, task complexity, and data characteristics that inform more effective project scoping design and guideline development. 
 
Evaluate which tasks and data types benefit most from automation and work with customers to optimize against. 
 
Translate behavioral insights and empirical trends into optimized project structures, ensuring our annotation workflows are designed for both efficiency and quality before projects launch. 
 
Partner with cross-functional teams to design, run, and analyze A/B experiments, establishing best practices for project structure. 
 
Contribute to capacity forecasting and optimization by converting quantitative decision-making into forecast drivers and scenarios. 
 
Identify key factors that lead to improving productivity and quality. 
 
Contribute to development of a holistic view of analyst behaviors across the various platforms, and identify synergies that drive a more positive analyst experience and efficiency gains 
 
Preferred Qualifications 
 
Masters degree or PhD in Computer Science, Statistics, Mathematics, Engineering, Economics or related field. 
 
Experience with the deployment of Large Language Models / Generative AI in service of efficiency in operations 
 
Excellent communication and presentation skills with meticulous attention to detail and the ability to collaborate effectively between business and analytic teams at multiple levels of the organization 
 
Passion for AIML and Operations, with a consistent track record of operational results. 
 
Minimum Qualifications 
 
Bachelors degree in Computer Science, Statistics, Mathematics, Engineering, Economics or related field. 
 
4+ years of experience in data science with proven skills in developing meaningful and concise analytic objectives from general business goals 
 
Tested capabilities and comfort in scalable schema designs, relational database and big data technologies, ETL, code management, and query performance optimization 
 
Mastery in SQL-based languages, and proficiency in at least one large-scale data languages 
 
Strong hands-on experience interpretable with machine learning models and sophisticated analytic solutions using scripting tools such as Python or R 
 
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 $172,100 and $258,600, 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.

Data Scientist, AIML Data Scientist

The Health AI team is at the forefront of machine learning and health science at Apple. We are a close-knit team of highly accomplished, deeply technical research scientists, software engineers and machine learning engineers passionate about delivering innovative technologies that impact millions of users. We are looking for a senior engineer passionate about solving real-world problems in the health domain that make a difference in our customers' lives. 
 
Description 
 
In this role, you will use your skills and experience in ML and deep learning to design, implement, tune and evaluate machine learning models and algorithms to solve ambitious problems involving unique data and objectives including state of the art generative AI models and tools. The successful candidate should possess excellent interpersonal skills and ability to work multi-functionally to apply novel research at the intersection of Health and ML into customer features. 
 
Preferred Qualifications 
 
PhD preferred. 
 
5+ years experience in hands-on experience in state-of-the-art machine learning and deep learning as applied to large-scale datasets. 
 
Strong background in generative models, natural language processing, and large language models. 
 
Proficiency working with large scale models using modern machine learning packages (e.g. TensorFlow, PyTorch, Jax, Huggingface). 
 
Ability to thrive in fast-paced environment, deal with uncertainty, and adapt to new and changing requirements. 
 
Proven track record of contributing to diverse teams in a collaborative environment. 
 
A passion for building outstanding and innovative products. This position involves a wide variety of interdisciplinary skills. 
 
Minimum Qualifications 
 
10+ years of overall software development experience. 
 
Experience in leading a team and track record of multi-functional collaboration to deliver customer-facing features in production. 
 
BS/MS/Ph.D. in Computer Science, Computer Engineer, Machine Learning, or related fields or equivalent qualification. 
 
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 $212,000 and $386,300, 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- Health AIML

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. 
 
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. 
 
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 $147,400 and $272,100, and your base pay will depend on your skills, qualifications, experience, and location. 
 
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits. 
 
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

AIML - Machine Learning Engineer, Data and ML Innovation

Join the Siri team at Apple! Build and contribute to a product and company that that is building products, personal devices, and software designed to enrich people&rsquo;s lives. Work on building and advancing the world&rsquo;s most popular intelligent assistant that helps millions of people get things done - just by asking. 
 
Global Siri works to take Siri to the next level of intelligence and capabilities in all languages and markets. We build machine learning models, systems, and software that understands the intents hundreds of millions of users and their billions of requests to Siri, on Apple devices such as iPhone, iPad, Apple Watch, Mac, AirPods, HomePod, Vision Pro and Apple TV. On the Global Scaling, Data, and Tools team, we work on ML modeling and algorithms, data platforms and technologies, and end-to-end ML product engineering to surprise and delight customers around the world in the languages that they speak. 
 
Description 
 
We seek a Senior Machine Learning Engineer / Tech Lead who is passionate about collaborating across teams in Siri and Apple to design, build, and deploy world-class machine learning systems that help Siri best serve the needs of our users. In this role, you will work on creating and improving the accuracy, speed, reliability, and capability of Global Siri&rsquo;s models and systems. We are particularly interested in &ldquo;full-stack&rdquo; machine learning engineers with strong experience in research, software engineering, and have strong leadership potential. 
 
You should be passionate about building outstanding products, and using the full spectrum of your skills to drive technical and organizational advancements. The ideal candidate is equally comfortable with the latest academic/research advancements in ML, LLMs, NLP, and related areas, diving into all parts of the full engineering/machine learning stack to diagnose user-facing issues and develop principled solutions, and deeply engaging in product metrics and goals with product managers, designers, and executives. Software engineering experience with both server-based and client-side (e.g. on-device) models is a definite asset. In this role, the ability to communicate complex technical ideas to diverse audiences, including research scientists, data scientists, engineers, designers, managers, and other stakeholders across Siri and Apple is also essential. 
 
This position involves a wide variety of skills and innovation. In addition to your individual technical contributions, there are immense opportunities to multiply the impact those around you by mentoring, motivating and challenging engineers to deliver features at high quality. If you are looking for a role that is challenging, impactful, has immense growth opportunities, this role is for you. 
 
Preferred Qualifications 
 
Experience in data science and analytics, including data annotation, statistical analyses, A/B testing, and/or conducting experiments and investigations in large-scale usage data environments 
 
Self-starter with a proven ability to handle multiple projects with strict deadlines 
 
Experience in the iOS development ecosystem (e.g. Swift, Objective-C, CoreML, or SiriKit) is a plus 
 
Experience in localization, internationalization, machine translation, or language technologies is an asset 
 
Minimum Qualifications 
 
Master's or PhD degree in computer science, software engineering, machine learning, language technologies, or related fields; outstanding candidates with Bachelor's degrees and multiple years years of significant engineering/product experience will also be considered 
 
10+ years of experience developing, shipping, and measuring industry-scale machine learning-based software systems; experience working on large-scale NLU systems a strong asset. 
 
Experience as a senior engineer, tech lead, or engineering manager for a machine learning-based product, including mentoring other engineers, working with program and product managers, and communicating accomplishments, metrics, and challenges to cross-functional stakeholders and leaders 
 
Expertise and experience in Large Language Models (LLMs) or other foundation models, ideally demonstrated through publications or shipping foundation model-based features and products. 
 
Strong background in machine learning, deep learning, and foundation models, as demonstrated through top-tier publications and/or successful development of training data, models, or software in commercial machine learning systems. 
 
Excellent software engineering skills: Proficiency in at least one object-oriented language (e.g. Java, C++, Objective-C, or Swift), scripting languages (e.g. Python, Ruby, bash), and deep learning/machine learning frameworks (e.g. TensorFlow, PyTorch, or CoreML) 
 
Outstanding problem solving, critical thinking, creativity, organizational, design, and interpersonal skills; ability to work with all levels of engineers, scientists, designers, and communicate effectively with management, leadership, and cross-functional partners 
 
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant . 
 
Pay &amp; Benefits 
 
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $181,100 and $318,400, and your base pay will depend on your skills, qualifications, experience, and location. 
 
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits. 
 
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

Sr. Machine Learning Engineer, Siri Global

Explore 105+ Aiml machine learning engineer mlr in Cupertino this March. Find roles across top companies and apply now to boost your career.