aiml - machine learning engineer, data and ml innovation

aiml - sr machine learning engineer - data and ml innovation

aiml - sr machine learning engineer, data and ml innovation

administrative assistant, hardware technology

ai software and security engineer Jobs in Cupertino

ai software and security engineer

ai/ml engineer, applied data science Jobs in Cupertino

ai/ml engineer, applied data science

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

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

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

machine learning engineer

Apple

Apple&rsquo;s Health Sensing team is seeking a versatile Machine Learning Engineer to develop next-generation health algorithms that deliver meaningful insights to users by combining classical ML, signal processing, and emerging generative AI techniques. Our team has delivered impactful features including heart rate notifications, ECG, blood oxygen, sleep apnea notifications, and overnight vitals to millions of Apple Watch users. 
 
Description 
 
This role is ideal for an engineer who enjoys moving quickly from idea to prototype to product, creatively overcoming data limitations, and applying new tools to multi-modal sensor fusion problems in health and wellness. You will work across the full algorithm lifecycle including data strategy, modeling, evaluation, optimization, and deployment.&quot;,&quot;responsibilities&quot;:&quot;Develop and validate ML and GenAI-driven algorithms for health sensing applications from concept through productization 
 
Prototype and compare multiple approaches using real and synthetic data to accelerate algorithm development 
 
Design experiments and evaluation methodologies to quantify performance and guide algorithm improvements 
 
Optimize algorithms for robustness, efficiency, and on-device deployment constraints 
 
Work cross-functionally with user studies, hardware, software, and product teams to bring algorithms into product 
 
Analyze failure modes, quantify tradeoffs, and drive data-driven algorithm improvements 
 
Preferred Qualifications 
 
Experience developing algorithms for physiological sensing using multi-modal data 
 
Familiarity with on-device ML frameworks or resource-constrained optimization 
 
Experience working with incomplete, noisy, or limited datasets 
 
Background in experimental design and statistical validation 
 
Experience with distributed or cloud-based ML workflows 
 
Experience accelerating development through simulation, synthetic data, or creative data augmentation approaches 
 
Self-driven, curious engineer comfortable taking ambiguous sensing problems from concept to working solutions 
 
Minimum Qualifications 
 
Bachelors degree in Computer Science, Electrical Engineering, Biomedical Engineering, Statistics, Applied Mathematics, or related field, or equivalent industry experience. 
 
Strong foundation in machine learning, statistics, signal processing, or applied mathematics for real-world sensing problems 
 
Experience applying modern AI techniques, including generative AI and agentic AI, to accelerate algorithm development, data generation, and performance evaluation 
 
Proficiency in Python for algorithm development and optimization 
 
Demonstrated ability to rapidly prototype, evaluate multiple approaches, and iterate based on experimental results 
 
Experience owning algorithm development from early exploration through validation and integration 
 
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant . 
 
Pay &amp; Benefits 
 
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $139,500 and $258,100, and your base pay will depend on your skills, qualifications, experience, and location. 
 
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits. 
 
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

Machine Learning Engineer

<div>The Software Localization &amp; Engineering team powers the tooling, features and processes used to create an exceptional localized experience for Apple&rsquo;s international customers. We are responsible for the readiness and high quality of Apple features internationally across all of Apple&rsquo;s products. 
 
We are in search of a creative, motivated, and passionate technical leader who has a robust understanding of large language models (LLMs), generative AI, Natural Language Processing (NLP) and Machine Translation (MT). An ideal candidate has the ability to lead diverse cross-functional efforts to build the next generation of ML tooling, processes and end-user features for international locales. Strong engineering fundamentals and a passion for this area are required. 
 
Description 
 
As a Machine Learning Engineer in the International Data Engineering team, you will join a phenomenal team of passionate engineers to design, implement and qualify Apple Intelligence features globally across a wide variety of Apple&rsquo;s products. We are looking for an exceptional candidate to help architect the future of localizing and scaling Machine Learning models and datasets. Your duties include: 
 
<ul><li>Actively engaging in all aspects of model development, from ideation, training, experimentation, evaluation to deployment</li></ul> 
<ul><li>Helping define a scalable, data driven quality program to continuously improve ML based products and features globally</li></ul> 
<ul><li>Collaborating with translation, Localization quality, project management and engineering teams to develop and scale the approach with a focus on the end user and the product quality</li></ul> 
<ul><li>Developing and maintaining features, frameworks and tools to help facilitate the software translation process</li></ul> 

Preferred Qualifications 
 
Hands-on experience with handling large datasets and developing data analytics pipelines for natural language based products 
 
Proven ability to comprehend, interpret, and apply cutting-edge research into consumer-oriented products 
 
Proficiency using open-source ML toolkits and frameworks (e.g. PyTorch, TensorFlow, OpenNMT) 
 
Experience in software Localization / internationalization 
 
Native-level foreign language skills in reading, writing and speaking 
 
Experience or curiosity in languages and culture, comfortable working cross-functionally and cross-culturally 
 
Published research in the field of Machine Learning or AI 
 
Minimum Qualifications 
 
Experience with Machine Learning (ML), with a particular emphasis on Large Language Models (LLMs) and Natural Language Processing (NLP) 
 
Hands-on experience developing end to end machine learning systems: defining and creating metrics and datasets, training models and performing error triaging 
 
Comprehensive knowledge and hands-on experience with fine-tuning approaches and training models 
 
Strong programming skills in Python or other scripting languages 
 
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>

Machine Learning Engineer, International Data 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'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

Would you like to be a part of Apple&rsquo;s AI and Machine Learning org, where we encourage and create groundbreaking technology for multi-modal models with strong agent and reasoning capabilities? The Data and Machine Learning Innovation (DMLI) team is seeking a passionate Machine Learning Engineer to explore new methods, challenge existing metrics and protocols, and develop new insightful practices for real-world ML challenges. As a team member, you will work on some of the most ambitious technical challenges in the field. Your role will involve collaborating closely with our team of machine learning researchers, engineers, and data scientists. Together, you will spearhead groundbreaking research initiatives and develop transformative products designed to build for billions of users worldwide. 
 
Description 
 
As a Machine Learning (ML) Engineer, you will be entrusted with the critical role of innovating and applying innovative research in foundation models to with a particular focus on audio data. This includes working across the full ML pipeline-from pre-training on large-scale unlabeled audio corpora to post-training evaluation and fine-tuning with task-specific datasets. The solutions you develop will have a significant impact on future Apple software and hardware products, as well as the broader ML ecosystem. 
 
Your responsibilities will extend to designing and developing a comprehensive multi-modal data generation and curation framework for foundation models at Apple. You will also contribute to building robust model evaluation pipelines that support continuous improvement and performance assessment. In addition, the role involves analyzing multi-modal data to better understand its influence on model behavior and outcomes. Furthermore, you will have the opportunity to showcase your groundbreaking research work by publishing and presenting at premier academic venues. 
 
YOUR WORK MAY SPAN VARIOUS APPLICATIONS, INCLUDING: 
 
Designing self-supervised and semi-supervised representation learning pipelines, and fine-tuning strategies for tasks like speech recognition and speaker identification. 
 
Applying data selection techniques such as novelty detection and active learning across multi modalities to improve data efficiency and reduce distributional gaps. 
 
Modeling data distributions using ML/statistical methods to uncover patterns, reduce redundancy, and handle out-of-distribution challenges. 
 
Rapidly learning new methods and domains as needed, and guiding product teams in selecting effective ML solutions. 
 
Preferred Qualifications 
 
Deep understanding of multi-modal foundation models. 
 
Staying up-to-date with emerging trends in generative AI and multi-modal LLMs. 
 
The ability to formulate machine learning problems, design, experiment, implement, and communicate solutions effectively with multi-functional teams. 
 
Demonstrated publication records in relevant conferences (e.g., CVPR, ICCV, ECCV, NeurIPS, ICML, ICLR, etc.). 
 
Track records of adopting ML to solve cross-disciplinary problems. 
 
Minimum Qualifications 
 
Deep technical skills in one or more machine learning areas, such as computer vision, audio, combinatorial optimization, causality analysis, natural language processing, and deep learning. 
 
Strong software development skills with proficiency in Python; hands-on experience working with deep learning toolkits like PyTorch, TensorFlow, or JAX (one of). 
 
5+ years of experience developing and evaluating ML applications, demonstrating a passion for understanding and improving model/data quality.&lsquo; 
 
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant . 
 
Pay &amp; Benefits 
 
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $147,400 and $272,100, and your base pay will depend on your skills, qualifications, experience, and location. 
 
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits. 
 
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

AIML - Sr Machine Learning Engineer - Data and ML Innovation

Do you want to play a part in the revolution in Foundation Models? Contribute to model hillclimbing for Apple Intelligence features that leverage Apple Foundation Models, and work with the people who built the intelligent products that helps millions of people get things done - just by asking or typing? 
 
The vision for AIML FM Data organization is to improve Foundation Models by leveraging data and cutting-edge LLM techniques. As a Sr ML Engineering on the team, you will drive ML innovations, identify key opportunity areas and experiment with various techniques to improve model training and evaluation efficiency and performance. 
 
Description 
 
As a Senior Machine Learning Engineer, you will join end-to-end development of large language models and agentic systems, from training pipelines to evaluation frameworks and production deployment. 
 
You will work at the intersection of modeling, infrastructure, and product, helping push model quality through systematic experimentation and iteration. 
 
You&rsquo;ll collaborate closely with research, infrastructure, and product teams to design robust training pipelines, build agent environments, and ship high-impact AI capabilities into real-world applications. 
 
This role blends deep modeling expertise with strong engineering fundamentals and offers the opportunity to shape both the technical direction and the ML platform powering Apple products.&quot;,&quot;responsibilities&quot;:&quot;Model Training &amp; Optimization 
 
Design and implement large-scale LLM pretraining and post-training pipelines, including supervised fine-tuning, preference optimization, and continual learning. 
 
Drive model hillclimbing through disciplined experimentation: dataset curation, hyperparameter tuning, and ablation studies. 
 
Work on scalable training workflows using distributed frameworks. 
 
Evaluation, Reward, and Data Systems 
 
Develop evaluation frameworks for both offline benchmarks and online metrics, covering reasoning, tool use, and task success. 
 
Design and maintain verifiers / rubric-based reward systems for agentic tasks and model alignment. 
 
Build data pipelines for data generation, filtering, labeling, and replay buffers. 
 
Agent &amp; Environment Infrastructure 
 
Build and maintain agent training environments, including tool APIs, simulators, and sandboxed runtimes. 
 
Implement environment abstractions to support reinforcement learning and agent evaluation at scale. 
 
Collaborate on large scale RL-infra: RL-trainer, rollout system, and containerized environments. 
 
Preferred Qualifications 
 
Direct experience with agentic systems, including tool use, environment design, or reinforcement learning. 
 
Experience with building or operating training environments or simulators (gym-style, tool-based, or sandboxed environments). 
 
Experience with model hillclimbing workflows: systematic experimentation, ablations, dataset iteration, and continuous quality improvement. 
 
Ability to work across research and engineering boundaries, turning ideas into scalable systems. 
 
Have demonstrated creative and critical thinking with an innate drive to improve how things work. Have a high tolerance for ambiguity. 
 
Minimum Qualifications 
 
5+ years of hands on ML engineering experiences, with at least 1+ years working directly on large language models or generative AI. 
 
Bachelor&rsquo;s, Master&rsquo;s, or PhD in Computer Science, Machine Learning, or a related technical field - or equivalent practical experience. 
 
Hands-on experience with LLM training workflows, including one or more of: Pretraining or continued pretraining, Supervised fine-tuning (SFT), Preference optimization (e.g., RLHF, DPO, PPO). 
 
Strong software engineering fundamentals: debugging, testing, code reviews, and production reliability. 
 
Demonstrated publication records in relevant conferences (e.g., NeurIPS, ICML, ICLR, etc.). 
 
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant . 
 
Pay &amp; Benefits 
 
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $147,400 and $272,100, and your base pay will depend on your skills, qualifications, experience, and location. 
 
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits. 
 
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

AIML - Sr Machine Learning Engineer, Data and ML Innovation

The Intelligence Platform team empowers clients across Apple&rsquo;s operating systems with a high quality user-centric search and data platform, and the primary inference platform that enable next generation user experiences for Apple Intelligence. We are in search of an accomplished and driven Machine Learning Engineer who has a robust understanding of Large Language Models, Generative AI and high-performance systems computing. Your primary role will involve working with our cross-functional teams that build foundation models, as well as our client teams that want to run inference using these models and continue the development of our inference stack. By contributing to our team, you&rsquo;ll play an integral part in developing Siri, Photos, Music, and various other services, leaving a significant footprint on the evolution of our AI platforms. Join us in our exciting journey as we push the frontiers of Machine Learning and Generative AI. Your expertise and contributions will be invaluable in shaping the future of our Intelligence Platform. 
 
Description 
 
As a Machine Learning Engineer on the Apple Intelligence Platform Inference Tean, you&rsquo;ll join a phenomenal team of top-performing engineers and and will be entrusted with a range of responsibilities. Your tasks will include: 
 
Leading the exploration and application of Large Language Models and Generative AI, venturing into new areas within these fields. 
 
Translating the latest research into high-performing systems and a model serving stack that can be practically applied to enhance user experiences. 
 
Contribute to setting the team&rsquo;s strategic direction, cultivating an environment that encourages innovation and professional growth. 
 
Collaborating with various teams to develop and implement evolving requirements of our clients on the GenAI inference stack, ensuring performance optimization and alignment with broader business goals. 
 
Preferred Qualifications 
 
An advanced degree (Master&rsquo;s or Ph.D.) in Computer Science, Artificial Intelligence, Machine Learning, or a related field is required 
 
Ongoing professional development in Machine Learning and Artificial Intelligence domains is expected. 
 
Minimum Qualifications 
 
In-depth experience in Machine Learning, with a particular emphasis on Large Language Models (LLMs) and Generative AI. 
 
Published research in the field of Machine Learning or AI is highly desirable, indicating an ability to not only understand but also contribute to cutting-edge research. 
 
Proven ability to comprehend, interpret, and apply cutting-edge research into tangible applications. 
 
Proven problem-solving and leadership abilities, with the capacity to steer the team&rsquo;s research and practical applications in a collaborative and fast-paced environment. 
 
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant . 
 
Pay &amp; Benefits 
 
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $147,400 and $272,100, and your base pay will depend on your skills, qualifications, experience, and location. 
 
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits. 
 
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

Machine Learning Engineer - Large Language Models & Generative AI Inference

At Apple, we blend world-class hardware, software, and services to produce a tight ecosystem of products used by billions of people around the world. 
 
Machine Learning and AI models are integrated throughout our ecosystem to enhance the user experience. Ensuring a delightful end to end user experience requires well-thought out data curation, rigorous evaluation methodology, and a high signal north star metric. 
 
Guiding feature development across the entire product life cycle requires partnering closely with modeling teams, engineers, design, and others. At Apple&rsquo;s scale, it&rsquo;s paramount that methods scale across platforms, user-model mediums, and languages. 
 
Description 
 
Advance the performance of Apple Intelligence Large Language Models, across Apple platforms, languages, and modalities. 
 
Advise the data training and product roadmap for Foundation Models. Source novel datasets and run ablation studies to inform training hill-climbing. 
 
Identify high signal relevant public benchmark datasets to guide model development. Prototype and productionalize LLM-based applications to improve model development life cycle. 
 
Design detailed evaluation methodologies in close partnership with engineering and product teams to support critical go/no-go decisions. 
 
Develop and evangelize robust metrics for hillclimbing. Regularly present to partner teams and executive sponsors, both at a technical and high level. 
 
Preferred Qualifications 
 
Strong communication skills and experience persuading both technical audiences and high level executive audiences. 
 
Passion for Apple products. 
 
Minimum Qualifications 
 
Bachelors degree and 7+ years of work experience in Data Science, Machine Learning, or Engineering. 
 
Experience training and evaluation LLMs. 
 
Strong intuition for metrics, including their strengths and shortcomings. 
 
A track record of positive impact on shipped products. 
 
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 - Sr Machine Learning Engineer, Modeling Evaluation & Data

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