ai researcher

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

artificial intelligence specialist

Decompute

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 Company Description
 
 
 
 
 
 Decompute is a pioneer in the development of AI models optimized for local environments, requiring as little as 1 GB of VRAM. Known for our BlackBird platform, which enables the creation of on-device AI agents, we specialize in areas such as finance, legal, coding, and creative tasks like voice and image generation. Our breakthrough multimodal AI models are renowned for outperforming cloud-dependent competitors, even while operating entirely offline on consumer-grade devices. With a model footprint as small as 350M parameters, Decompute&rsquo;s solutions are efficient, scalable, and tailored for CPUs and GPUs. Join us in revolutionizing on-device AI as we empower enterprises with next-generation advancements in technology.
 
 
 
 
 
 
 Role Description
 
 
 
 
 
 This is a full-time, on-site role located in Cupertino, CA, for an AI Researcher. The AI Researcher will lead cutting-edge research in artificial intelligence, focusing on the development and optimization of advanced models for on-device use. Daily responsibilities include conducting in-depth research, designing algorithms, implementing machine learning solutions, analyzing datasets, and collaborating with cross-functional teams to innovate and refine AI systems.
 
 
 
 
 
 
 Qualifications
 
 
 
 
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 <li>
 Strong foundation in ML and CS, including model architectures, programming and algorithm design
 </li>
 </ul>
 
 Experience training, evaluating, and improving advanced models in production or research settings
 
 <ul>
 <li>
 Experience in Research and implementation of AI-focused technologies
 </li>
 <li>
 Proficiency in Statistics for data analysis and model evaluation
 </li>
 <li>
 Strong problem-solving capabilities and aptitude for innovation
 </li>
 <li>
 Good communication skills for collaboration and presentation of research insights
 </li>
 <li>
 Experience with on-device AI or resource-efficient machine learning is a plus
 </li>
 <li>
 Ph.D. or Master's degree in Computer Science, Artificial Intelligence, or related field preferred
 </li>
 </ul>
</div>

AI Researcher

Apple

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

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

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

At Apple, we believe privacy is a fundamental human right. Our Security Engineering &amp; Architecture (SEAR) organization is at the forefront of protecting billions of users worldwide, building security into every product, service, and experience we create. 
 
The SEAR ML Security Engineering team combines cutting-edge machine learning with world-class security engineering to defend against evolving threats at unprecedented scale. We're responsible for developing intelligent security systems for Apple Intelligence that protect Apple's ecosystem while preserving the privacy our users expect and deserve. 
 
We're seeking a staff-level ML Security Research Scientist who operates at the intersection of applied research and production impact. You'll lead original security research on agentic ML systems deployed at scale-driving secure agentic design directly into shipping products, identifying real vulnerabilities in tool-using models and designing adversarial evaluations that reflect actual attacker behavior. You'll work at the boundary between research, platform engineering, and product security, translating findings into architectural decisions, launch requirements, and long-term hardening strategies that protect billions of users. Your impact will be measured by risk reduction in production systems that ship. 
 
Description 
 
This role focuses on applied security research for production ML systems, with an emphasis on agentic and tool-using models deployed at scale. You will lead research efforts that surface real security risks in shipped or near-shipped systems, and you will drive mitigations that integrate cleanly into Apple&rsquo;s ML platforms and products. 
 
You will operate at the boundary between research, platform engineering, and product security, conducting original research grounded in real system behavior and translating it into concrete design changes, launch requirements, and long-term hardening strategies. Impact is measured by risk reduction in production, not theoretical results alone. 
 
&quot;,&quot;responsibilities&quot;:&quot;Lead applied research on production agent systems: Conduct original security research on deployed agentic ML systems that interact with tools, APIs, memory, workflows, and sensitive data. Identify and characterize vulnerabilities such as indirect prompt injection, tool misuse, privilege escalation, goal hijacking, and cross-context data leakage, and develop defenses validated under production constraints. 
 
Design realistic adversarial evaluations: Build and maintain adversarial testing frameworks that reflect real attacker incentives and system complexity, including multi-step, cross-tool, and persistence-based attacks that surface failure modes missed by standard evaluations. 
 
Drive defenses into shipping systems: Develop mitigations that are compatible with production requirements around latency, reliability, debuggability, and privacy. Influence architectural choices such as capability scoping, isolation boundaries, execution control, and runtime enforcement. 
 
Own threat models for agent deployments: Define trust boundaries and threat models for agentic ML across Apple platforms and services, and translate them into actionable security requirements and release criteria. 
 
Bridge research and engineering: Partner deeply with ML platform teams, product engineering, and product security to ensure research insights become design guidance, test infrastructure, and launch blockers where appropriate. 
 
Provide technical leadership: Set standards for applied ML security research, mentor other researchers, and influence how agent systems are reviewed, built, and released across the organization. 
 
Preferred Qualifications 
 
Experience researching or securing LLM-based or tool-augmented ML systems. 
 
Ability to work fluidly across research, engineering, and security review processes. 
 
Track record of influencing production systems through research-driven insights. 
 
Publications in top venues are a plus, but production impact is the primary signal. 
 
Minimum Qualifications 
 
Ph.D. or equivalent experience in machine learning, security, systems, or a related field. 
 
Demonstrated experience in applied ML security, adversarial ML, or systems security with real-world impact. 
 
Strong experimental and engineering skills, with an emphasis on reproducibility and operational relevance. 
 
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.

Research Scientist, Applied Machine Learning Security (Agent Systems)

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

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

Explore 19+ Artificial intelligence specialist in Cupertino this April. Find roles across top companies and apply now to boost your career.