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machine learning engineer ii

Uber

<div>About the Role
 
 
Have you ever ordered a car service on Uber, and when the ride arrives, wondered how it got to you so fast? Ever ordered food on UberEats and wondered where the driver was before receiving your order and how long it took to get to the restaurant or if your order was ready when the courier arrived? Ever wondered why your grocery delivery from Uber always has the best apple picked?
 
 
If so, Uber is for you. In our ML and Science division, we strive to make magic within Uber's marketplace. This requires judgment to make difficult trade-offs, blending algorithms with human resourcefulness, and the ability to build simplicity from complexity. When we get the balance right for everyone, Uber magic happens. We build systems to peer into the future to craft the most cost-efficient marketplace for matching supply and demand. We are passionate about using innovative economics, machine learning, and scalable distributed software that automates and optimizes every aspect of this intricate dance between participants of the marketplace.
 
 
We are involved in every stage of the product development cycle and use data to inform product decisions, build models to power our solutions, and also develop platform tools that are used across teams with a primary focus on Mobility and Delivery. We work with millions of earners across the globe to make this magic happen and want you to join us!
 
 
About the Team
 
 
Earners (drivers and couriers) are an integral part of Uber's multi-sided marketplace. They provide the time and the means to move people and things. Importantly, they enable the connection between the physical and digital world to make the movement happen at the push of a button for everyone, everywhere.
 
 
Within Uber, Earner plays a critical role in earners' journey as the team is responsible for earner onboarding, activation, early life cycle, and resurrection. This presents the teams with the opportunity to shape and tailor the product experience during earners' many firsts (i.e., first time interacting on the Uber platform, choosing the earning opportunity, going online, receiving incentive offers, completing a trip, or reading the earnings summary). These firsts can be daunting.
 
 
Therefore, making sure that the earner journey is great at every touch point is important to build trust with Earners, communicate Uber's value proposition, and ensure each firsts to be a great experience.
 
 
The team employs a variety of ML/AI techniques, spanning from causal ML meta learners, supervised ML, RL multi-armed bandits, genAI LLMs, transformer modeling on sequential data to deep learning embeddings to build impactful data products.
 
 
What the Candidate Will Need / Bonus Points
- What the Candidate Will Do - 
 
 
<ul><li>Build statistical, optimization, and machine learning models
</li><li>Develop innovative new earner incentives that earners for choosing our network and optimizing Uber's new earner incentives spend
</li><li>Optimize Uber's background check spend and onboarding funnel
</li><li>Design recommendation engines to recommend the most relevant earning opportunities and early lifecycle content
</li><li>Develop matching algorithms for driver to driver mentorship program
</li><li>Model and predict earner behaviors to improve earner experience throughout the onboarding funnel
</li><li>The team employs a variety of ML/AI techniques, spanning from causal ML meta learners, supervised ML, RL multi-armed bandits, genAI LLMs, transformer modeling on sequential data to deep learning embeddings to build impactful data products.
</li><li>Work closely with multi-functional leads to develop technical vision, new methodological approaches, and drive team direction.
</li><li>Collaborate with cross-functional teams such as product, engineering, operations, and marketing to drive ML system development end-to-end from conceptualization to final product.
</li></ul>- Basic Qualifications - 
 
 
<ul><li>PhD, Master or equivalent experience in Computer Science, Machine Learning, Operations Research, Statistics, or other related quantitative fields or related field
</li><li>2 years minimum of industry experience as a Machine Learning Engineer/Research Scientist with a strong focus on deep learning and probabilistic modeling.
</li><li>Proficiency in multiple object-oriented programming languages (e.g. Python, Go, Java, C++).
</li><li>Experience with any of the following: Spark, Hive, Kafka, Cassandra.
</li><li>Experience building and productionizing innovative end-to-end Machine Learning systems.
</li><li>Experience in exploratory data analysis, statistical modeling, hypothesis testing, and experimental design.
</li><li>Experience working with cross-functional teams(product, science, product ops etc).
</li></ul>- Preferred Qualifications - 
 
 
<ul><li>3+ years of industry experience in machine learning, including building and deploying ML models.
</li><li>Publications at industry recognized ML conferences.
</li><li>Experience in modern deep learning architectures and probabilistic modeling.
</li><li>Experience with optimization techniques, including reinforcement learning (RL), Bayesian methods, causal ML meta learners, genAI LLM.
</li>Expertise in the design and architecture of ML systems and workflows. 
<li>
</li></ul> 
 
 
 
For New York, NY-based roles: The base salary range for this role is USD$171,000 per year - USD$190,000 per year. For San Francisco, CA-based roles: The base salary range for this role is USD$171,000 per year - USD$190,000 per year. For Seattle, WA-based roles: The base salary range for this role is USD$171,000 per year - USD$190,000 per year. For Sunnyvale, CA-based roles: The base salary range for this role is USD$171,000 per year - USD$190,000 per year. For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award &amp; other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits. More details can be found at the following link https://jobs.uber.com/en/benefits.</div>

Machine Learning Engineer II

Apple

The Applied Machine Learning team builds production multimodal systems that understand and transform large-scale image, audio, and video content. Our work spans diffusion-based image generation, transcription and diarization, face and object detection, OCR and image description for search, and automated quality control of media pipelines. 
 
We are looking for a Staff Machine Learning Engineer to strengthen our diffusion and video models, adapt small and mid-sized LLMs, and turn our uniquely large corpus of weakly labeled media into a durable product advantage. This is an opportunity to shape the next generation of multimodal experiences end-to-end, from data and models to evaluation and user impact. 
 
Description 
 
The Staff Machine Learning Engineer - Multimodal Generation &amp; Post-Training will be a senior individual contributor on a small, applied ML team focused on production multimodal systems. The role will lead fine-tuning and adaptation of diffusion and emerging video models, as well as post-training of small and medium LLMs for captioning, moderation, and retrieval-friendly descriptions. 
 
The engineer will design data and evaluation workflows that use our large archive of weakly labeled music, podcast, film, TV, and short-form content to drive measurable quality and efficiency improvements. The role includes close collaboration with partner infra teams for model serving and with adjacent product and research groups to bring new capabilities into production. 
 
Preferred Qualifications 
 
PhD in Computer Science, Machine Learning, or a related technical field. 
 
8+ years of industry experience with production multimodal systems spanning image, audio, and/or video. 
 
Deep expertise with diffusion and video generation techniques (e.g., ControlNet/IP-Adapter, temporal consistency methods, sampling and latency optimization). 
 
Experience with PEFT/QLoRA and post-training approaches such as DPO or related preference-based methods for small and mid-sized LLMs. 
 
Background in ASR/VAD/diarization, OCR, multimodal retrieval, or face recognition with fine-grained temporal alignment. 
 
Familiarity collaborating with infra/platform teams on model serving (e.g., batching strategies, quantization, observability) and translating requirements into reliable production deployments. 
 
Demonstrated ability to define metrics, build evaluation harnesses, and communicate results clearly to cross-functional partners. 
 
Track record of publications, patents, or open-source contributions in relevant areas of machine learning or multimodal modeling. 
 
Minimum Qualifications 
 
Master&rsquo;s degree in Computer Science, Electrical Engineering, or a related technical field, or equivalent practical experience. 
 
5+ years of hands-on industry experience building and shipping machine learning systems to production. 
 
Proven experience training and fine-tuning diffusion or other image/video generative models, including adapter-based methods such as LoRA. 
 
Proficiency in Python and at least one major deep learning framework such as PyTorch. 
 
Experience designing and operating ML pipelines for noisy or weakly labeled data, including offline evaluation and monitoring in production. 
 
Strong software engineering skills, including code quality, experimentation discipline, and debugging/profiling of model performance. 
 
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 $201,300 and $302,200, 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.

Staff Machine Learning Engineer, Apple Services 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&rsquo;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. 
 
&quot;,&quot;responsibilities&quot;:&quot;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. 
 
Experience of multimodal large language model or image/video generation model training is a plus. 
 
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 $171,600 and $302,200, 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

<div>
 
 Summary
 
 
 
 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.
 
 
 
 Minimum Qualifications
 
 
 
 <ul>
 <li>
 Demonstrated expertise in computer vision, natural language processing, and machine learning with a passion for data-centric machine learning.
 </li>
 <li>
 Deep understanding in multi-modal foundation models.
 </li>
 <li>
 Staying on top of emerging trends in generative AI and multi-modal LLM.
 </li>
 <li>
 Strong programming skills and hands-on experience using the following languages or deep learning frameworks: Python, PyTorch, or Jax.
 
 
 </li>
 </ul>
 
 Preferred Qualifications
 
 
 
 <ul>
 <li>
 3+ years of experience with developing and evaluating ML applications, and demonstrated experience in understanding and improving data quality.
 </li>
 <li>
 Strong publication record in relevant conferences (e.g. CVPR, ICCV, ECCV, NeurIPS, ICML, ICLR, , etc)
 </li>
 <li>
 Strong problem-solving and communication skills.
 </li>
 <li>
 Ph.D/MS degree in Machine Learning, Natural Language Processing, Computer Vision, Data Science, Statistics or related areas
 
 
 </li>
 </ul>
 
 Pay &amp; Benefits
 
 
 
 At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $147,400 and $272,100, and your base pay will depend on your skills, qualifications, experience, and location.
 
 
 Apple employees also have the opportunity to become an Apple shareholder through participation in Apple&rsquo;s discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple&rsquo;s Employee Stock Purchase Plan. You&rsquo;ll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses &mdash; including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits.
 
 
 Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
 
 
 Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant.
 
 
 Apple accepts applications to this posting on an ongoing basis.
 
 
</div>

AIML - Machine Learning Engineer, Data and ML Innovation

Join Apple&rsquo;s Information Security Machine Learning (ISML) team, where we are redefining cybersecurity through data-driven intelligence. Our mission is to transform traditional reactive security measures into autonomous systems that proactively detect and defend against threats. We achieve this through cutting-edge research, applied science, and robust infrastructure development. We are seeking a highly motivated and talented Machine Learning Engineer to join our dynamic and growing team. You will play a pivotal role in designing, developing, and deploying machine learning models that power our advanced security products and services. This is an incredible opportunity to make a real world impact by building intelligent systems that detect and prevent advanced threats, enhance critical security processes, and protect Apple and our customers. 
 
Description 
 
The Security ML Engineer will bring their expertise in machine learning to the problems and opportunities facing Information Security at Apple. You will contribute to the Autonomous Security program by developing production ready AI/ML systems using Apple&rsquo;s internal platforms, cloud services, and local compute environments. 
 
You will translate research to design, building and deploying machine learning models for security use cases, leveraging generative AI, statistical modeling, reinforcement learning, and data science to address complex security challenges. You will collaborate with cross-functional teams including security teams, software engineers, and researchers to prototype and scale AI/ML driven security solutions. You will own end-to-end ML workflows: data exploration, model development, evaluation metrics design, deployment, and monitoring. 
 
Preferred Qualifications 
 
Ph.D. in a technical field such as Computer Science, Engineering, Statistics, or related disciplines. 
 
In-depth knowledge of ML algorithms, including supervised/unsupervised learning, deep learning (CNNs, RNNs, LSTMs), and large language models. 
 
Industry experience in deploying ML and generative AI solutions in cybersecurity contexts. 
 
Familiarity with cloud platforms (e.g., AWS, GCP) and their security offerings is a plus. 
 
Experience with large scale data processing and analysis using tools such as Apache Spark. 
 
Experience working in a key security process, such as Incident Response, Threat Intelligence, or Vulnerability Management. 
 
Experience with specific security tools and technologies (e.g., SIEM, IDS/IPS, endpoint security solutions). 
 
Contributions to open-source security or machine learning projects. 
 
Publications or talks at top-tier ML or security conferences. 
 
Additional proficiency in C++ or Swift is a plus 
 
Minimum Qualifications 
 
BSc or Masters degree in Machine Learning, Data Science, Computer Science, Information Security, Mathematics, Statistics, or related field. 
 
Strong programming skills in Python and Scala; experience with ML libraries such as TensorFlow, PyTorch, HuggingFace, and Scikit-learn. 
 
Hands-on experience with full ML model lifecycle: from experimentation to deployment and monitoring. 
 
Solid grasp of security fundamentals including network security, incident response, threat modeling, and vulnerability management. 
 
Excellent written and verbal communication skills, with the ability to present technical concepts clearly to varied audiences. 
 
Familiarity with CI/CD workflows and ML pipelines . 
 
Experience operating, and scaling production services in cloud native environments. 
 
Experience deploying models on CUDA devices using tools like TensorFlow or Torch. 
 
Proven experience building generative AI applications for real-world use cases. 
 
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant . 
 
Pay &amp; Benefits 
 
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $139,500 and $258,100, and your base pay will depend on your skills, qualifications, experience, and location. 
 
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits. 
 
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

Machine Learning Engineer, Information Security

Are you excited about building innovative generative AI experiences that empower millions of users daily? Do you thrive in collaborative environments and enjoy applying your machine learning expertise to real-world user experiences? If so, we&rsquo;d love to hear from you. We&rsquo;re looking for a Senior Machine Learning Engineer to join the Apple Intelligence Data Platform team. This team powers key intelligence features across Apple&rsquo;s ecosystem - including Siri Suggestions, the Shortcuts app, and more - by building scalable, privacy-conscious ML systems! Our team is responsible for the Research, Development and Deployment of the core platform that powers Apple Intelligence on device and on private compute cloud - adapters, speculative decoding, guided generation to name a few. Our team is responsible for underpinning all the Apple Intelligence features we shipped to our customers including Writing Tools, Notification Summaries, ChatGPT integration, Siri and more. Our team has a great mix of talent across Machine Learning and Software Engineering. We love to share our knowledge within our team, stay abreast of state-of-the-art and deliver outstanding products for our users. We also have a strong culture of multi-functional collaboration across teams at Apple. Proactive Intelligence is central to Apple Intelligence. We&rsquo;re building a contextual, on-device platform that anticipates user needs - from predicting which app you'll launch next to understanding the difference between work and leisure modes. This is your opportunity to help shape the next generation of personal, privacy-preserving intelligence for millions of users! https://www.apple.com/apple-intelligence/ (https://www.apple.com/apple-intelligence/) 
 
Description 
 
As an engineer on the Apple Intelligence Data Platform team, you will work on developing and integrating foundational components for on-device and cloud-based intelligence. You will focus on designing, building, and deploying scalable agent systems that understand your context and personal knowledge. Your work will directly influence how users interact with Apple products through context-aware, proactive, and personalized experiences. This role is ideal for candidates with hands-on experience in Vector databases, Knowledge Graphs, Semantic Search, Retrieval-Augmented Generation (RAG), decoding strategies, Generative AI inference, and prompt optimization. You will collaborate closely with several engineering teams at Apple -such as Accessibility, Hardware, Human Interface, NLP, Privacy, etc- to power exciting Apple Intelligence features and ship them to our customers. 
 
Preferred Qualifications 
 
MS or Ph. D in Computer Science or a related field 
 
Deep understanding of machine learning and deep learning algorithms 
 
Experience in LLM, machine learning, deep learning, information retrieval or natural language processing 
 
Strong analytical and independent problem-solving skills 
 
Experience working in cross-functional teams across product, design, and infrastructure 
 
Minimum Qualifications 
 
5+ years of increasing responsibility and relevant experience 
 
Bachelor's Degree or higher in Computer Science, Artificial Intelligence, Machine Learning, Information Retrieval, Data Science or a related field. 
 
Experience in Knowledge Graphs (KG), RAG systems, integration of LLMs with external memories, Vector databases and related fields. 
 
Excellent software design, problem solving, critical thinking and collaborative skills including written and verbal communication 
 
Proficiency in one or more of the following languages: Python, Go, Java, C++, or Swift 
 
Ability to understand/clarify product requirements and translate them into technical tasks in ML modeling and 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 $139,500 and $258,100, and your base pay will depend on your skills, qualifications, experience, and location. 
 
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits. 
 
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

Senior Machine Learning Engineer, Apple Intelligence Data Platform

<div>The Machine Intelligence, Neural Design (MIND) team, part of Apple&rsquo;s AIML organization, is leading Apple-wide innovation on HW/SW co-design for efficient inference. With roots in ML, computer vision, and energy efficiency research, our team is strategically positioned to contribute to diverse initiatives ranging from shipping features in well-known Apple products to ambitious, long-term research projects. 
 
We are seeking a hands-on Machine Learning Engineer to drive the data &amp; evaluation lifecycle for our production models. In this role, you will focus on designing and scaling high-performance data processing pipelines, ensuring data quality, performing in-depth failure analysis on production models, and implementing advanced data augmentation techniques to boost model performance. This includes but is not limited to crafting creative techniques to analyze audio &amp; video datasets, designing metrics to understand user behavior &amp; evaluate performance of machine learning models. You will innovate across the entire end-to-end ML production pipeline, bridging the gap between hardware, software, and modeling, ensuring our ML systems are robust, efficient, and scalable. 
 
Description 
 
We are seeking a Machine Learning Engineer to design and deliver innovative features and models that advance our ML systems. In this role, you will scale model evaluation workflows, build robust data pipelines, and optimize performance across the stack. 
 
Your responsibilities will include: 
 
<ul><li>Pipeline Scaling &amp; Optimization: Design, build, and maintain scalable ETL/ELT data pipelines using tools like Spark, &amp; Airflow to handle large-scale datasets. Optimize existing pipelines for efficiency, latency, and cost.</li></ul> 
<ul><li>Data Augmentation &amp; Synthesis: Research and implement advanced data augmentation techniques (e.g., GANs, semantic augmentation, synthetic data generation) to address data scarcity and imbalanced datasets.</li></ul> 
<ul><li>Data Quality &amp; Monitoring: Implement data observability and automated data validation checks to identify data drift, schema violations, and outliers in real-time.</li></ul> 
<ul><li>Failure Analysis &amp; Debugging: Perform root-cause analysis on production model failures, diagnosing issues between data inputs and model outputs using advanced statistical methods.</li></ul> 
<ul><li>Model Evaluation: Collaborate with other machine learning engineers to productize models, implementing robust evaluation frameworks, including experimentation and performance monitoring.</li></ul> 

Preferred Qualifications 
 
Experience with shipping ML features and products 
 
Experience with GPU-based distributed training &amp; evaluation. 
 
Background in Computer Vision (image augmentation), Audio and Natural Language Processing. 
 
Minimum Qualifications 
 
Proficiency in working with unstructured data, specifically video &amp; audio signals, for object detection, pattern recognition, feature extraction and segmentation. 
 
Proficiency with Python and deep learning frameworks like PyTorch. 
 
Expertise in designing metrics, and conducting metric change &amp; performance analysis for model evaluation. 
 
Strong problem solving skills in analyzing complex, ambiguous problems and clearly presenting sophisticated technical concepts to both expert and non-expert audiences. 
 
Proven track record of contributing to cross functional projects in a collaborative environment. 
 
Self-motivated and curious with creative and critical thinking capabilities and drive to figure out and improve how things work. 
 
High tolerance for ambiguity. You find a way through. You anticipate. You connect and synthesize. 
 
Strong verbal and written communications skills with demonstrated experience in authoring &amp; presenting analytical insights via papers &amp; presentations. 
 
Experience with large scale training ML models including deep learning based models. 
 
Experience with shipping ML features and products. 
 
Master&rsquo;s degree or equivalent experience in a technical or quantitative field. 
 
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant . 
 
Pay &amp; Benefits 
 
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $139,500 and $258,100, and your base pay will depend on your skills, qualifications, experience, and location. 
 
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits. 
 
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.</div>

AIML - Machine Learning Engineer - Computer Vision & Audio, MIND

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