aiml - machine learning research engineer, data and machine learning innovation

aiml - sr applied ai scientist - genai model autograding, evaluation

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gen ai research engineer Jobs in Cupertino

gen ai research engineer

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

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

ai research scientist

Apple

Apple's System Intelligence and Machine Learning (SIML) team is seeking a senior Generative AI expert to pioneer the next generation of human-centric device interaction and multimodal scene understanding. You will be at the core of our efforts to develop multimodal LLMs that can perceive and understand complex scenes and nuanced human interactions, behaviors, and preferences. This is a unique opportunity to join a leading applied research group known for its foundational contributions to Apple Intelligence, where you will focus on the end-to-end lifecycle of generative models-from novel architecture design and large-scale training to final deployment. 
 
Description 
 
We are looking for a senior applied scientist with strong ML and Generative modeling skills who can design, train, and deploy multimodal GenAI technology. You will need to learn quickly and implement and demonstrate new user experiences using large foundation models. You will build novel and innovative technology, forge collaborations with cross-functional partners, and adapt and iterate your solutions in a dynamic environment. 
 
You will be expected to advance human interaction and scene understanding modeling across various fronts, from a system level to a core ML algorithm level. Some of the myriad challenges include understanding user behavior and preferences from interactions with the device and the environment, retrieving useful and nuanced information based on past interactions, handling deeply interleaved streaming inputs, reasoning over varying temporal contexts, developing memory systems to enable long-term adaptation, and generating semantically rich internal representations to enable open-ended downstream tasks. 
 
You will be responsible for delivering ML models and solutions that can readily be adopted in production pipelines, such as APIs for production-ready ML models and algorithms well-integrated into our training infrastructure.&quot;,&quot;responsibilities&quot;:&quot;Design, train, and deploy large-scale multimodal LLMs, owning the entire lifecycle from initial architecture to final deployment within the constraints 
 
Implement and demonstrate novel, human-centric user experiences by applying the capabilities of large foundation models 
 
Create robust, scalable ML models and APIs that can be well-integrated into Apple's production pipelines and training infrastructure 
 
Work closely with partner teams to build, iterate, and adapt innovative solutions in a dynamic, product-focused environment 
 
Preferred Qualifications 
 
Proven track record of deploying innovative ML technologies in production 
 
Familiarity with developing ML for resource-constrained devices 
 
Experience working with large cross-functional and diverse teams 
 
Minimum Qualifications 
 
PhD or Masters Degree in Computer Science, Engineering, or a related field with a focus on machine learning; or equivalent experience 
 
Strong research skills with first author publications in top tier ML conferences 
 
Expert-level knowledge of SOTA in large auto-regressive transformer models, multi-modal encoders, and representation learning 
 
Experience with multimodal large language models (LLMs) 
 
Strong programming skills in Python, maintaining ML code bases grounded in software engineering principles 
 
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.

Generative AI Applied Scientist, SIML - ISE

<div>The Information Intelligence team is creating groundbreaking technology for artificial intelligence, machine learning and natural language processing! The features we create are redefining how hundreds of millions of people use their computers and mobile devices to search and find what they are looking for. Our universal search engine powers search features across a variety of Apple products, including Siri, Spotlight, Safari, Messages and Lookup. We also develop state-of-the-art generative AI technologies based on Large Language Models to power innovative features in both Apple&rsquo;s devices and services on the cloud. 
 
As part of this group, you will be doing large scale machine learning and deep learning research and development to improve Open Domain Question Answering (using both structured knowledge graph data and unstructured web data) and Summarization as well as developing fundamental building blocks needed for Artificial Intelligence. This involves developing sophisticated machine learning and large language models (LLMs) to understand user queries, retrieve and rank relevant documents across multiple sources and synthesize information across documents to provide user with a direct answer that best satisfies their intent and information seeking needs. Additionally, you will research and develop the state-of-the-art LLMs for summarizing personal data such as emails, messages, and notifications. 
 
You will also work with researchers and data scientists to develop, fine-tune, and evaluate domain specific Large Language Models for various tasks and applications in Apple&rsquo;s AI powered products and conduct applied research to transfer the cutting edge research in generative AI to production ready technologies. 
 
Description 
 
As a member of our fast-paced group, you&rsquo;ll have the unique and rewarding opportunity to shape upcoming products from Apple. We are looking for highly motivated machine learning engineers and researchers having strong machine learning and deep learning fundamentals with hands-on experience in fine-tuning deep learning and large language models. This role will have the following responsibilities: 
 
<ul><li>Conduct research and development on state-of-the-art deep learning and large language models for various tasks and applications in Apple&rsquo;s AI-powered products</li></ul> 
<ul><li>Developing, fine-tuning, and evaluating domain-specific Large Language Models for various NLP tasks including summarization, question answering, search relevance/ranking, entity linking and query understanding problems</li></ul> 
<ul><li>Conducting applied research to transfer the cutting edge research in generative AI to production ready technologies</li></ul> 
<ul><li>Understanding product requirements, translate them into modeling tasks and engineering tasks</li></ul> 
<ul><li>Stay up to date with the latest advancements and research in deep learning and large language models</li></ul> 

Preferred Qualifications 
 
PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related field. 
 
At least 1 year of experience in various state-of-the-art techniques related to LLM fine-tuning in 1 or more of the following areas: 
 
<ul><li>Supervised Fine-tuning (SFT) with Rejection Sampling</li></ul> 
<ul><li>Preference-based fine-tuning techniques (e.g RLHF, Reward model, DPO, PPO, GRPO etc.)</li></ul> 
<ul><li>Parameter efficient fine-tuning techniques (e.g LoRA)</li></ul> 
<ul><li>Hallucination reduction and factual accuracy improvements</li></ul> 
<ul><li>Designing and implementing safety guardrails</li></ul> 
At least 4 years of experience with large-scale model training, optimization, and deployment 
 
One or more scientific publications in various conferences and journals 
 
Outstanding communication and interpersonal skills with ability to work with cross-functional teams. 
 
Minimum Qualifications 
 
Master&rsquo;s in Computer Science, Artificial Intelligence, Machine Learning, or a related field. 
 
2 years of experience in various state-of-the-art techniques related to LLM fine-tuning in 1 or more of the following areas: Supervised Fine-tuning (SFT) with Rejection Sampling, Preference-based fine-tuning techniques (e.g RLHF, Reward model, DPO, PPO, GRPO etc.), Parameter efficient fine-tuning techniques (e.g LoRA), Hallucination reduction and factual accuracy improvements, Designing and implementing safety guardrails 
 
Experience working with Deep learning or LLM model development for various NLP tasks and RAG applications including prompt engineering, training data collection and generation, model fine-tuning and model evaluation 
 
Experience working with Python and at least one of the deep learning frameworks such as TensorFlow, 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 $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.</div>

Machine Learning Engineer, Apple Search & Knowledge Platforms

<div>
 
 Summary
 
 
 
 The Health Personalization team builds outstanding technologies to support AI-driven health experiences that provide our users with understandable, actionable information about their health and wellbeing, and support them to achieve their health and wellness goals. As part of the larger Sensor Software &amp; Prototyping team, we take a multimodal approach using a variety of sensors and user data signals across hardware platforms, such as camera, wearables, and natural language user input. We are committed to building deeply personal features that understand, anticipate, and adapt to users&rsquo; behaviors and uphold Apple&rsquo;s deep commitment to privacy as a fundamental human right. Our team values expertise, innovation, and inclusivity. Come join us!
 
 
 
 Description
 
 
 
 In this role, you will develop, evaluate, and continuously improve Generative AI systems for real-world health and wellbeing applications. You&rsquo;ll apply deep expertise in health-focused machine learning alongside rigorous evaluation methodology. Your work will directly shape customer-facing health products by turning evaluation results into scalable pipelines that drive data-informed model improvements across the full ML lifecycle. You&rsquo;ll collaborate with a fast-growing team of top scientists and engineers to build generative systems that meet the highest standards of quality, reliability, and alignment with human intent.
 
 
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Develop and improve generative AI systems for health and wellbeing applications across the full feature development lifecycle.
 </li>
 <li>
 Independently design, run, and analyze ML experiments to deliver measurable quality improvements.
 </li>
 <li>
 Design and implement evaluation frameworks&mdash;including automated assessment tools, LLM-based autograders, and benchmarks&mdash;with rigorous validation of their reliability and validity.
 </li>
 <li>
 Apply statistical and interpretability methods to analyze evaluation data and model behavior, identify failure modes through adversarial testing and failure analysis, and drive actionable improvements.
 </li>
 <li>
 Build and maintain scalable, reusable pipelines for inference, training, and evaluation, integrated with large-scale data workflows.
 </li>
 <li>
 Work cross-functionally with engineers, clinical experts, designers, and hardware and software teams to bring features into production with real-world applicability and impact.
 
 
 </li>
 </ul>
 
 Minimum Qualifications
 
 
 
 <ul>
 <li>
 BS and a minimum of 3 years relevant industry experience
 </li>
 <li>
 Proficiency in Python and ability to write clean, performant code and collaborate using standard software development practices.
 </li>
 <li>
 Technical expertise and hands-on experience crafting and evaluating machine learning solutions for user-facing applications.
 </li>
 <li>
 Experience applying a scientific approach to drive machine learning innovation: developing hypotheses, designing experimentation strategies, and guiding data generation / collection / evaluation (e.g. user studies, annotation workflows, A/B tests).
 
 
 </li>
 </ul>
 
 Preferred Qualifications
 
 
 
 <ul>
 <li>
 MS and a minimum of 3 years of relevant industry experience or PhD in relevant fields.
 </li>
 <li>
 Strong communication skills, comfort working with multiple engineering teams on complex projects, and experience contributing to an inclusive team culture.
 </li>
 <li>
 Technical expertise in generative AI domains, such as large language model architectures, memory representation, planning, knowledge retrieval, natural language understanding.
 </li>
 <li>
 Hands-on experience developing complex generative AI systems in an applied setting, e.g. experience with post-training techniques like supervised fine-tuning, adapter training, and reinforcement learning from human feedback.
 </li>
 <li>
 Experience with LLM-based evaluation systems and rigorous, evidence-based approaches to test development, e.g. quantitative and qualitative test design, reliability and validity analysis.
 </li>
 <li>
 Customer-focused mindset with experience or strong interest in building consumer digital health and wellness products.
 </li>
 <li>
 Knowledge of health informatics or experience with complex health data sources (e.g. EHRs, medical ontologies, wearables)
 </li>
 <li>
 Experience with building and deploying performant and scalable systems (full-stack)
 
 
 </li>
 </ul>
 
 Pay &amp; Benefits
 
 
 
 At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $147,400 and $272,100, and your base pay will depend on your skills, qualifications, experience, and location.
 
 
 Apple employees also have the opportunity to become an Apple shareholder through participation in Apple&rsquo;s discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple&rsquo;s Employee Stock Purchase Plan. You&rsquo;ll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses &mdash; including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits.
 
 
 Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
 
 
 Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant.
 
 
 Apple accepts applications to this posting on an ongoing basis.
 
 
</div>

Gen AI Research Engineer

Our team of applied ML scientists and engineers works to enhance the experience and productivity of software development at Apple. Our team applies state-of-the-art ML models to solve real-world problems in software quality and development workflows. We're looking for talented and enthusiastic team members to join us in our efforts. If this sounds like you, we have many challenging and interesting problems to work on together and would love to talk to you! 
 
Description 
 
Our team designs and builds ML solutions to transform how Apple and developers in the ecosystem approach developing quality software at scale. We are a team of applied scientists, infrastructure engineers, and machine learning engineers who work with NLP, computer vision, and multimodal domains to create AI-powered testing solutions. 
 
In this role, you will be responsible for developing novel ML approaches to challenging quality problems at scale. You'll work hands-on with a diverse set of ML techniques to find what actually works in production. You'll guide technical direction for the team, mentoring junior engineers while maintaining deep involvement in the code and experimentation yourself. Your technical judgment and understanding of both generative models and traditional ML methods will directly shape our product direction. 
 
You will be successful and feel fulfilled in our team if you enjoy tackling challenging problems with creative solutions, have strong intuition for what will and won't work in practice, and thrive in a collaborative team setting where you can both learn and teach.&quot;,&quot;responsibilities&quot;:&quot;Design and implement novel ML solutions for testing and automation problems 
 
Provide technical leadership and mentorship on research directions 
 
Apply a broad range of ML techniques (LLMs, classical ML, computer vision, reinforcement learning) to identify the best approach for each problem 
 
Work cross-functionally with product teams, integration engineers, and other ML practitioners across Apple 
 
Preferred Qualifications 
 
Experience with classical ML techniques, reinforcement learning, or probabilistic modeling in addition to deep learning 
 
Experience in NLP, computer vision, or multimodal ML applications 
 
Track record of technical mentorship or leading complex ML projects 
 
Familiarity with Apple development ecosystem and frameworks 
 
Experience with testing, software quality, or developer tools 
 
Minimum Qualifications 
 
5+ years of hands-on experience developing machine learning systems in production environments 
 
Strong programming skills with demonstrated ability to write production-quality ML code 
 
Proven track record working with multiple ML paradigms including modern and traditional methods 
 
MS or PhD in Computer Science, Machine Learning, or equivalent professional experience 
 
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant . 
 
Pay &amp; Benefits 
 
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $181,100 and $318,400, and your base pay will depend on your skills, qualifications, experience, and location. 
 
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits. 
 
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

Senior Machine Learning Engineer - Tools & Frameworks AI

The Health Personalization team builds outstanding technologies to support AI-driven health experiences that provide our users with understandable, actionable information about their health and wellbeing, and support them to achieve their health and wellness goals. As part of the larger Sensor Software &amp; Prototyping team, we take a multimodal approach using a variety of sensors and user data signals across hardware platforms, such as camera, wearables, and natural language user input. We are committed to building deeply personal features that understand, anticipate, and adapt to users&rsquo; behaviors and uphold Apple&rsquo;s deep commitment to privacy as a fundamental human right. Our team values expertise, innovation, and inclusivity. Come join us! 
 
Description 
 
In this role, you will develop, evaluate, and continuously improve Generative AI systems for real-world health and wellbeing applications. You&rsquo;ll apply deep expertise in health-focused machine learning alongside rigorous evaluation methodology. Your work will directly shape customer-facing health products by turning evaluation results into scalable pipelines that drive data-informed model improvements across the full ML lifecycle. You&rsquo;ll collaborate with a fast-growing team of top scientists and engineers to build generative systems that meet the highest standards of quality, reliability, and alignment with human intent.&quot;,&quot;responsibilities&quot;:&quot;Develop and improve generative AI systems for health and wellbeing applications across the full feature development lifecycle. 
 
Independently design, run, and analyze ML experiments to deliver measurable quality improvements. 
 
Design and implement evaluation frameworks-including automated assessment tools, LLM-based autograders, and benchmarks-with rigorous validation of their reliability and validity. 
 
Apply statistical and interpretability methods to analyze evaluation data and model behavior, identify failure modes through adversarial testing and failure analysis, and drive actionable improvements. 
 
Build and maintain scalable, reusable pipelines for inference, training, and evaluation, integrated with large-scale data workflows. 
 
Work cross-functionally with engineers, clinical experts, designers, and hardware and software teams to bring features into production with real-world applicability and impact. 
 
Preferred Qualifications 
 
MS and a minimum of 3 years of relevant industry experience or PhD in relevant fields. 
 
Strong communication skills, comfort working with multiple engineering teams on complex projects, and experience contributing to an inclusive team culture. 
 
Technical expertise in generative AI domains, such as large language model architectures, memory representation, planning, knowledge retrieval, natural language understanding. 
 
Hands-on experience developing complex generative AI systems in an applied setting, e.g. experience with post-training techniques like supervised fine-tuning, adapter training, and reinforcement learning from human feedback. 
 
Experience with LLM-based evaluation systems and rigorous, evidence-based approaches to test development, e.g. quantitative and qualitative test design, reliability and validity analysis. 
 
Customer-focused mindset with experience or strong interest in building consumer digital health and wellness products. 
 
Knowledge of health informatics or experience with complex health data sources (e.g. EHRs, medical ontologies, wearables) 
 
Experience with building and deploying performant and scalable systems (full-stack) 
 
Minimum Qualifications 
 
BS and a minimum of 3 years relevant industry experience 
 
Proficiency in Python and ability to write clean, performant code and collaborate using standard software development practices. 
 
Technical expertise and hands-on experience crafting and evaluating machine learning solutions for user-facing applications. 
 
Experience applying a scientific approach to drive machine learning innovation: developing hypotheses, designing experimentation strategies, and guiding data generation / collection / evaluation (e.g. user studies, annotation workflows, A/B tests). 
 
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant . 
 
Pay &amp; Benefits 
 
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $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.

This role sits at the intersection of health, technology, and human potential, shaping how ordinary people understand, manage, and improve their well-being. As Senior Clinical AI Product Scientist, you will help transform real-world health insights into foundation models that empower individuals to make meaningful, sustainable changes in their daily lives. Your work will not only guide the technical direction of groundbreaking health AI systems, it will advance a more supportive, accessible, and human-centered future for everyone seeking to live healthier. 
 
Description 
 
The Senior Clinical AI Product Scientist in Health AI will serve as a pivotal leader in the intersection of clinical medicine, machine learning, and product development. You define and drive the technical and product requirements for next-generation foundational AI systems that serve healthcare providers, patients, caregivers, and consumers. Leveraging your deep product and technical experience in machine learning and , you will lead end-to-end development of health foundation models for medical record processing, clinical workflows, and patient-facing applications. You will conduct stakeholder research across clinical domains, architect AI systems in healthcare settings, define validation and evidence-generation frameworks, and make informed technical decisions from research through production deployment.&quot;,&quot;responsibilities&quot;:&quot;Lead cross-functional teams (data science, machine learning engineering, clinical informatics) to develop foundational AI systems in the healthcare domain. 
 
Define product strategy and technical requirements novel AI health models and their application in user products and research. 
 
Conduct user research and discovery with stakeholders (clinicians, informaticists, patients, caregivers) to identify real-world problems and translate them into actionable product and ML requirements.. 
 
Design and execute evaluation frameworks to ensure high reliability, regulatory compliance, and adoption of AI solutions in healthcare. 
 
Mentor and lead teams: supervise ML scientists and engineers, provide technical leadership, ensure best practices in ML, product design, and usability. 
 
Maintain thought leadership: represent the organization at conferences, publish or present work, track emerging trends in health AI / LLMs and drive innovation. 
 
Preferred Qualifications 
 
Advanced degree (e.g., M.S., Ph.D.) in Computer Science. 
 
Experience working with electronic health record (EHR) systems and clinical natural language processing (NLP) applications 
 
Track record of developing and deploying foundational LLMs/AI models in consumer settings. 
 
Experience designing and conducting evaluation. 
 
Familiarity with product development, regulation, and privacy considerations, in the health/life sciences field. 
 
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 
 
Minimum of 10 years of experience in healthcare AI/ML or intelligent systems/ML with demonstrated expertise in ML, or large language models (LLMs), or foundation models in the healthcare domain. 
 
Proven track record of leading machine learning project and taking AI systems from research through production deployment and adoption. 
 
Demonstrated experience coordinating across multiple functional areas (data science, clinical informatics, engineering) to deliver complex AI products. 
 
Bachelor&rsquo;s degree in Computer Science, or related area of study, or equivalent experience. 
 
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant . 
 
Pay &amp; Benefits 
 
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $203,300 and $365,400, 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 Clinical AI Product Scientist - Health AIML

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

Explore 69+ Ai research scientist in Cupertino this March. Find roles across top companies and apply now to boost your career.

69 ai research scientist jobs In Cupertino

Generative AI Applied Scientist, SIML - ISE

Machine Learning Engineer, Apple Search & Knowledge Platforms

Gen AI Research Engineer

Senior Machine Learning Engineer - Tools & Frameworks AI

Gen AI Research Engineer

Senior Clinical AI Product Scientist - Health AIML

Data Scientist, AIML Data Scientist