aiml - machine learning engineer, data and ml innovation

aiml - senior machine learning engineer - data science, responsible ai and safety

2026 spring business operation specialist + math content teacher

administrative assistant, hardware technology

administrative assistant, platform apps & technologies

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 - senior machine learning engineer - data science, responsible ai and safety Jobs in Cupertino

ai ml engineer applied data science

Apple

Imagine what you could do here. At Apple, new ideas have a way of becoming great products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. 
 
Are you passionate about taking AI from prototype to production at scale? 
 
Do you enjoy the craft of prompt engineering, retrieval optimization, and grounding? 
 
Can you build AI systems that are not just impressive demos, but reliable production tools? 
 
The Applied Data Science team within Legal Operations is building production-grade AI for a global legal organization. The AI/ML Engineer role is central to this mission - prototyping AI solutions, then scaling them to production systems that attorneys rely on every day. 
 
Description 
 
The AI/ML Engineer builds AI capabilities from prototype to production. You will develop prompt engineering solutions, RAG pipelines, AI agents, and evaluation frameworks - starting with rapid prototypes to validate use cases, then engineering them into scalable, production-grade systems. This role requires both the creativity to explore what's possible and the rigor to build what's reliable.&quot;,&quot;responsibilities&quot;:&quot;Prototype AI solutions to rapidly validate use cases and demonstrate feasibility 
 
Scale successful prototypes into production-grade systems with reliability, monitoring, and maintainability 
 
Implement prompt engineering solutions optimized for legal use cases 
 
Build and optimize RAG (Retrieval-Augmented Generation) pipelines using vector databases and knowledge graphs 
 
Develop context engineering approaches that leverage the semantic layer for improved accuracy 
 
Implement grounding mechanisms to reduce hallucinations and improve factual accuracy 
 
Build evaluation frameworks to measure AI accuracy, relevance, and safety across use cases 
 
Integrate AI capabilities with legal workflows (CLM, matter management, eBilling) 
 
Develop AI agent solutions for automation use cases across legal operations 
 
Implement guardrails and safety mechanisms for production AI systems 
 
Collaborate with AI Architect on system design and technical standards 
 
Support AI Product Developers with APIs, integration patterns, and technical guidance 
 
Preferred Qualifications 
 
Experience with LangChain, LlamaIndex, or similar LLM orchestration frameworks 
 
Experience with agentic AI frameworks (LangGraph, CrewAI, or similar) 
 
Familiarity with knowledge graphs and GraphRAG patterns 
 
Experience with AI evaluation tools (RAGAS, DeepEval, or similar) 
 
Knowledge of legal domain and legal NLP applications 
 
Experience with guardrails and safety frameworks (Guardrails AI, NeMo Guardrails) 
 
Understanding of MCP (Model Context Protocol) or similar integration patterns 
 
Experience deploying and monitoring AI systems at scale 
 
Track record of shipping AI products that users rely on 
 
Minimum Qualifications 
 
4+ years of delivering solutions in AI/ML engineering, NLP, or related roles 
 
Strong proficiency in Python and ML frameworks (PyTorch, TensorFlow, or similar) 
 
Experience with LLM APIs (OpenAI, Anthropic, or similar) 
 
Experience with RAG architectures and vector databases 
 
Understanding of prompt engineering techniques and best practices 
 
Experience taking AI systems from prototype to production 
 
Experience with evaluation frameworks for AI systems 
 
Supporting AI applications in production 
 
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.

AI/ML Engineer, Applied Data Science

We're seeking an experienced AI/ML Security Engineer to serve as both a hands-on technical expert and strategic business leader in securing our artificial intelligence and machine learning systems. This dual-function role requires someone who can dive deep into technical security challenges while effectively communicating risks, strategies, and solutions to cross-functional teams and executive leadership. 
 
We offer- 
 
Opportunity to shape AI/ML security strategy at global scale 
 
Collaborative environment that values diverse perspectives and inclusive leadership 
 
Professional development budget for conferences, training, and certifications 
 
Comprehensive benefits including mental health support and accessibility accommodations 
 
Description 
 
Design and implement comprehensive security frameworks for AI/ML pipelines, from data ingestion through model deployment 
 
Conduct security assessments of machine learning deployments, identifying vulnerabilities including adversarial attacks, data poisoning, and model inversion risks 
 
Develop automated security testing and monitoring solutions for AI/ML systems at scale 
 
Lead incident response for AI/ML security events, coordinating technical remediation and stakeholder communication 
 
Establish secure MLOps practices, including secure model versioning, access controls, and audit trails 
 
Collaborate with engineering teams to integrate security-by-design principles into AI/ML development workflows 
 
Business &amp; Strategic Leadership 
 
Translate complex AI/ML security risks into business impact assessments for leadership and stakeholders 
 
Develop and present security roadmaps that align with business objectives and product timelines 
 
Lead cross-functional teams through security initiatives, fostering collaboration between engineering, legal, privacy, and product teams 
 
Establish metrics and KPIs to measure AI/ML security posture and communicate progress to executives 
 
Preferred Qualifications 
 
Advanced degree in Computer Science, Cybersecurity, or related technical field 
 
Experience with differential privacy, federated learning, or other privacy-preserving ML techniques 
 
Background in threat modeling and security architecture design 
 
Familiarity with accessibility considerations in AI/ML systems 
 
Minimum Qualifications 
 
7+ years of experience in cybersecurity with 4+ years specifically in AI/ML security 
 
Proven track record of leading both technical teams and cross-functional business initiatives 
 
Deep understanding of machine learning security threats (adversarial ML, model stealing, data poisoning, etc.) 
 
Experience with secure cloud architectures and containerization technologies (Kubernetes, Docker) 
 
Strong background in at least two programming languages (Python, Swift, C++, or similar) 
 
Experience with ML frameworks (TensorFlow, PyTorch, Core ML) from a security perspective 
 
Demonstrated ability to communicate technical concepts to non-technical stakeholders 
 
Experience with regulatory compliance in AI/ML contexts (GDPR, CCPA, AI governance frameworks) 
 
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 Security 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

Imagine what you could do here. At Apple, new ideas have a way of becoming great products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. 
 
Are you passionate about translating AI capabilities into products that solve real legal problems? 
 
Do you thrive on understanding attorney and paralegal needs deeply - conducting interviews, mapping legal workflows, and documenting requirements? 
 
Can you bridge the gap between technical possibilities and legal business value? 
 
The Business Engineering team within Legal Operations is building AI-powered products for a global legal organization. The AI Product Owner role is central to this mission - bringing legal domain expertise, understanding user needs firsthand, defining what we build, and driving adoption across practice groups. 
 
Description 
 
The AI Product Owner defines and drives AI product strategy for Legal Operations, combining legal domain expertise with product ownership and hands-on business analysis. You will leverage your understanding of legal workflows to conduct user research, document requirements, own the product backlog, and work closely with AI/ML Engineers and AI Product Developers to deliver solutions that attorneys trust and adopt. This role requires legal operations fluency, deep empathy for users, analytical rigor, and sharp prioritization skills.&quot;,&quot;responsibilities&quot;:&quot;Support the product vision, strategy, and roadmap for AI products serving Legal Operations 
 
Leverage legal domain expertise to understand practice group workflows, terminology, and pain points 
 
Conduct user interviews, workflow analysis, and stakeholder sessions with attorneys, paralegals, and legal operations staff 
 
Document business requirements, legal process flows, and user stories with clarity and precision 
 
Define and prioritize the product backlog based on user needs, business value, and technical feasibility 
 
Translate legal workflows (matter management, contract lifecycle, outside counsel management, compliance) into clear product specifications 
 
Map current-state and future-state legal processes to identify automation and AI opportunities 
 
Collaborate with AI/ML Engineers to understand technical constraints and shape feasible solutions 
 
Work with AI Product Developers to design intuitive user experiences that drive adoption 
 
Facilitate requirements workshops, design sessions, and UAT with practice group stakeholders 
 
Define success metrics and measure product impact post-launch 
 
Conduct demos, gather feedback, and iterate based on user input 
 
Drive go-to-market planning including change management, training, and adoption strategies 
 
Communicate product roadmap, progress, and trade-offs to stakeholders and leadership 
 
Stay current on AI capabilities and legal tech trends to inform product direction 
 
Preferred Qualifications 
 
Direct experience in a corporate legal department, law firm, or legal tech company 
 
Familiarity with legal systems (matter management, CLM, eBilling, document management, eDiscovery) 
 
Understanding of legal spend management, LEDES/UTBMS billing codes, and outside counsel operations 
 
Experience with AI/ML products or data-driven applications 
 
Understanding of AI capabilities and limitations (LLMs, RAG, agents, prompt engineering) 
 
Experience with business process modeling and workflow documentation tools 
 
Experience with product analytics and user research methodologies 
 
Certified Scrum Product Owner (CSPO), CBAP, or similar certification 
 
JD, paralegal certificate, or legal operations certification a plus 
 
Track record of shipping products that legal professionals adopt and value 
 
Minimum Qualifications 
 
6+ years of experience in product management, business analysis, or legal operations - with hands-on experience across multiple disciplines 
 
Strong understanding of corporate legal department operations, workflows, and terminology 
 
Proven ability to conduct user research, document requirements, and translate findings into product specifications 
 
Experience working with technical teams (engineering, data science, AI/ML) 
 
Proven track record delivering solutions leveraging design thinking, agile methodologies, and the product development lifecycle 
 
Excellent documentation skills - able to produce clear business requirements, process flows, and user stories 
 
Strong facilitation skills for workshops, interviews, and stakeholder sessions 
 
Excellent communication skills - able to engage credibly with attorneys and influence stakeholders 
 
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 $137,900 and $207,300, and your base pay will depend on your skills, qualifications, experience, and location. 
 
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits. 
 
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

AI Product Owner, Legal Operations

Decompute

<div>
 
 
 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
 
 
 
 
 <ul>
 <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

Explore 35+ Ai ml engineer applied data science in Cupertino this May. Find roles across top companies and apply now to boost your career.