aiml - machine learning engineer, data and ml innovation

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

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ai software and security engineer Jobs in Cupertino

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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

machine learning engineer

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

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

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

Would you like to play a part in building the next generation of generative AI applications at Apple? We&rsquo;re looking for Machine Learning Engineers to work on ambitious projects that will impact the future of Apple, our products, and the broader world. This role is directed at assessing, quantifying, and improving the safety and inclusivity of Apple&rsquo;s Generative-AI powered features and products. In this role you&rsquo;ll have the opportunity to tackle innovative problems in machine learning, particularly focused on large language models for text generation, diffusion models for image generation, and mixed model systems for multimodal applications. As a member of Apple&rsquo;s Responsible AI group you will be working on a wide array of new features and research in the generative AI space. Our team is currently interested in large generative models for vision and language, with particular interest on Responsible AI, safety, fairness, robustness, explainability, and uncertainty in models. 
 
Description 
 
This role focuses on developing, carrying-out, interpreting, and communicating pre- and post-ship evaluations of the safety of Apple Intelligence features. Both human grading and model-based auto-grading are thoughtfully leveraged to power these evaluations. Additionally, this role researches and develops auto-grading methodology &amp; infrastructure to benefit ongoing and future Apple Intelligence safety evaluations. 
 
Producing safety evaluations that uphold Apple&rsquo;s Responsible AI values requires thoughtful data sampling, creation, and curation for evaluation datasets; high quality, detailed annotations and careful auto-grading to assess feature performance; and mindful analysis to understand what the evaluation means for the user experience. 
 
This role heavily draws on applied data science, scientific investigation and interpretation, cross-functional communication and collaboration, and metrics reporting and presentation.&quot;,&quot;responsibilities&quot;:&quot;Develop metrics for evaluation of safety and fairness risks inherent to generative AI features. 
 
Design datasets, identify data needs, and work on creative solutions, scaling and expanding data coverage through human and synthetic generation methods. 
 
Develop auto-grading technologies and approaches for application in safety evaluations of generative AI features. 
 
Provide technical direction and expertise to team-wide initiatives in safety auto-grading. 
 
Use and implement data pipelines, and collaborate cross-functionally to execute end-to-end safety evaluations. 
 
Work with highly-sensitive content with exposure to offensive and controversial content. 
 
Preferred Qualifications 
 
Experience working in the Responsible AI space. 
 
Prior scientific research and publication experience. 
 
Strong organizational and operational skills working with large, multi-functional, and diverse teams. 
 
Curiosity about fairness and bias in generative AI systems, and a strong desire to help make the technology more equitable. 
 
Minimum Qualifications 
 
MS, or PhD in Computer Science, Machine Learning, Statistics, or related fields; or an equivalent qualification acquired through other avenues. 
 
Experience working with generative models for evaluation and/or product development, and up-to-date knowledge of common challenges and failures. 
 
Strong engineering skills and experience in writing production-quality code in Python. 
 
Deep experience in foundation model-based AI programming (i.e.: using DSPy for optimizing foundation model prompts, for example) and a drive to innovate in this space. 
 
Experience working with noisy, crowd-based data labels and human evaluations. 
 
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 - Senior Machine Learning Engineer - Data Science, Responsible AI and Safety

Are you excited about using data to shape the experience of products used by hundreds of millions of people around the world? 
 
The Evaluation Data Engineering team, part of Apple&rsquo;s SWE organization, builds the scalable and reliable data platform that powers Siri, Search, and Machine Learning across Apple. 
 
We&rsquo;re looking for collaborative and mission-driven software engineers who care deeply about data quality, user impact, and building at scale. 
 
If you&rsquo;re passionate about tackling complex data challenges, eager to work with petabytes of data, and inspired by Apple&rsquo;s commitment to privacy and innovation, we&rsquo;d love to hear from you. 
 
Description 
 
In this role, you&rsquo;ll work cross-functionally across product and data science teams to build large-scale stream and batch processing data pipelines that power Analytics, Experimentation, and Machine Learning. 
 
You will design a unified and groundbreaking data processing framework using Flink, and/or Spark. 
 
Your work will focus on optimizing performance, ensuring data quality, and contributing to a long-term vision that extends the framework&rsquo;s capabilities to new user scenarios and groundbreaking machine learning applications. 
 
You will collaborate closely with Siri, Search, and other teams to design solutions that transform raw data into datasets that drive innovation. 
 
You&rsquo;ll automate dataset lifecycles with strong quality standards and help partners confidently use the data for product insights. 
 
Preferred Qualifications 
 
Strong in algorithms, data structures, data modeling, and SQL, with experience working on large-scale, complex, and high-dimensional datasets. 
 
Experience with machine learning algorithms or pipelines, particularly in the context of data engineering. 
 
Experience supporting ML engineers or data scientists with feature engineering or model data pipelines is a plus. 
 
Familiarity with testing tools and methodologies for validating large-scale, distributed data systems (e.g., data quality checks, pipeline testing frameworks, fault tolerance testing). 
 
Proven software engineering fundamentals, including experience with design, testing, version control, and CI/CD best practices. 
 
Comfortable working independently in a fast-paced, ambiguous environment. 
 
Excellent communication and problem-solving skills. 
 
Minimum Qualifications 
 
7+ years of experience designing, building, and maintaining distributed data processing systems at scale. 
 
5+ years of hands-on experience with stream and/or batch processing technologies such as Flink, Spark, Kafka, Airflow, Iceberg, and Trino. 
 
2-3 years of experience in full-stack development 
 
Proficient in at least one modern programming language (e.g., Java, Scala, and Python). 
 
MS or BS in Computer Science, Engineering, Math, Statistics, or a related field, or equivalent practical experience in data engineering. 
 
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 Software Data Engineer, Evaluation

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

Explore 21+ Machine learning engineer in Cupertino this May. Find roles across top companies and apply now to boost your career.