2026 fall applied science internship - reinforcement learning & optimization (machine learning) - united states, phd student science recruiting

aiml - applied ml engineer, data generation & verification

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data engineer

2026 fall applied science internship - reinforcement learning & optimization (machine learning) - united states, phd student science recruiting Jobs in Seattle

ai / software engineering intern Jobs in Seattle

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ai engineer - genai, creative-x Jobs in Seattle

ai engineer - genai, creative-x

aiml - applied ml engineer, data generation & verification Jobs in Seattle

aiml sr machine learning engineer data and ml innovation

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&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

Apple is where individual imaginations gather together, committing to the values that lead to great work. Every new product we build, service we create, or Apple Store experience we deliver is the result of us making each other&rsquo;s ideas stronger. That happens because every one of us shares a belief that we can make something wonderful and share it with the world, changing lives for the better. It&rsquo;s the diversity of our people and their thinking that inspires the innovation that runs through everything we do. When we bring everybody in, we can do the best work of our lives. Here, you&rsquo;ll do more than join something - you&rsquo;ll add something. 
 
As part of Apple&rsquo;s central data annotation engineering team, you&rsquo;ll help build the next generation of AI-powered user experiences. Our work provides high-quality datasets and expert feedback to train machine learning models and evaluate their performance across all products and verticals. The team maintains and develops a global distributed system that captures insights from human domain experts and analysts worldwide, operating at a scale that few companies can match. We leverage cutting-edge human-in-the-loop algorithms to create and curate datasets through fine-tuned multi-step annotation workflows and near real-time data quality feedback signals. You&rsquo;ll tackle complex challenges in ML data quality at unprecedented scale while collaborating closely with AIML engineering teams across the company. From Siri to the Photos app, from iPhone to Vision Pro, you&rsquo;ll help bring innovative experiences to millions of users worldwide. 
 
Description 
 
This role focuses on enhancing the annotation quality capabilities of Apple's central data annotation platform. You'll work on a cloud-based system that supports machine learning model development across all Apple products. The position combines backend engineering with research and concept development to improve how we measure, monitor, and optimize annotation and ML dataset quality at scale. You'll be responsible for building systems that ensure high-quality training data while developing innovative approaches to quality assessment and feedback mechanisms. 
 
As part of a close-knit team of half a dozen engineers focused on annotation quality initiatives and embedded in an even larger team of fellow data annotation engineers, you'll collaborate on shared challenges and contribute to collective problem-solving efforts. The team works together on overlapping projects, combining individual expertise in backend and frontend engineering, statistics, and ML to advance the state of annotation quality measurement and optimization. You'll have the opportunity to learn from peers tackling similar technical problems while contributing your own insights to push the boundaries of what's possible in large-scale data quality assessment. 
 
Your contributions will directly impact the foundation of Apple's AI and machine learning capabilities, ensuring that models across the entire product ecosystem are trained on the highest quality data possible.&quot;,&quot;responsibilities&quot;:&quot;Develop and maintain backend services for annotation quality measurement and monitoring systems 
 
Design and implement statistical measures and algorithms to assess annotation quality across diverse datasets incl. both foundational model driven and traditional approaches 
 
Create automated quality feedback mechanisms that provide real-time insights to annotation teams 
 
Research and prototype new approaches for improving annotation consistency and accuracy 
 
Optimize and design efficient data pipelines for dataset/annotation quality metrics collection 
 
Preferred Qualifications 
 
5+ years of experience in data annotation, data quality, or related ML value chain roles 
 
Experience building and scaling web-based platforms for machine learning workflows 
 
Advanced knowledge of statistical methods for data quality assessment 
 
Experience with distributed systems and microservices architecture 
 
Background in annotation workflow optimization 
 
Track record of research publications or patents in data quality or machine learning 
 
Experience working in cross-functional teams with both technical and non-technical stakeholders 
 
Minimum Qualifications 
 
PhD in Computer Science, Machine Learning, Statistics, Math, Physics or related field, or 5 years of equivalent work experience 
 
3+ years of backend engineering experience with cloud-based services 
 
Proficiency in Python and/or Golang for backend development 
 
Experience with AWS services including Lambda and RDS/Aurora 
 
Strong foundation in applied statistics and machine learning fundamentals 
 
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.

AIML - Applied ML Engineer, Data Generation & Verification

Capgemini

<div>
 
 
 Data Scientist
 
 
 
 Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you&rsquo;d like, where you&rsquo;ll be supported and inspired by a collaborative community of colleagues around the world, and where you&rsquo;ll be able to reimagine what&rsquo;s possible. Join us and help the world&rsquo;s leading organizations unlock the value of technology and build a more sustainable, more inclusive world.
 
 
 
 Job Description
 
 
 
 As a Data Scientist , you will lead the development and implementation of advanced data engineering solutions to support the deployment and optimization of Generative AI models. Your role will involve leveraging your extensive experience to design robust, scalable, and innovative data architectures that align with the unique requirements of General Artificial Intelligence (GenAI) applications.
 
 
 
 
 
 Key Responsibilities
 
 
 <ul>
 <li>
 The Machine Learning Engineer will be responsible for architectural design and planning, advanced data pipelines, model integration and optimization, scalability, performance and research and innovation supporting production generative AI systems.
 </li>
 <li>
 Production level ML workloads for customers using Databricks platform, including end-to-end ML pipelines, training/inference optimization, integration with cloud-native services and MLOps
 </li>
 <li>
 Build and maintain data engineering solutions on cloud platforms using hyperscaler services.
 </li>
 <li>
 Develop production-grade cloud (AWS/Azure/GCP) infrastructure that supports the deployment of ML applications, including drift monitoring
 </li>
 <li>
 Design, develop, and maintain data pipelines to efficiently collect, process, and load data from various sources into data storage systems (e.g., data warehouses, data lakes).
 </li>
 <li>
 Understanding indexing and vectorization to use with Generative AI prompt engineering.
 </li>
 <li>
 Strong understanding of fundamental data science concepts in NLP, including selection and understanding of embedding models.
 </li>
 <li>
 Use hyperscaler technologies to support data needs for expansion of Machine Learning/Data Science capabilities including generative AI.
 </li>
 <li>
 Design, develop, and implement scalable data pipelines and ETL/ELT processes using Python, PySpark and API integrations.
 </li>
 </ul>
 
 
 Required Skill and Experience
 
 
 
 
 <ul>
 <li>
 Bachelor's degree in computer science, data engineering, or a related field with 3+ year's experience (Master's preferred).
 </li>
 <li>
 Proven experience in data engineering, MLOps, ETL, and database management, QL and data manipulation languages.
 </li>
 <li>
 Azure, Python, Java, or Scala.
 </li>
 <li>
 data warehousing platforms (e.g., Databricks, Amazon Redshift, Snowflake) and big data technologies (e.g., Hadoop, Spark).
 </li>
 <li>
 highly scalable Data stores, Data Lake, Data Warehouse, Lakehouse, and unstructured datasets
 </li>
 </ul>
</div>

Data Scientist

NVIDIA

<div>
 NVIDIA seeks a senior software engineer to join the AI Networking co-design and benchmark R&amp;D team. In this pivotal role, the candidate is responsible for building and productizing machine learning tools. These include tools that use ML-based combinatorial optimization and build space exploration (DSE) techniques. These tools will be employed to optimize AI workloads across large GPU and CPU clusters, thereby ensuring the most efficient and productive utilization of system resources at data center scale. The role involves working on distributed Deep Learning, particularly within LLM training and inference stacks. A strong passion for collective communication and networking is desirable. The candidate will interact with diverse hardware and platforms, such as Host Channel Adapters (HCAs), Switches, CPUs, GPUs, and complete Systems.
 
 
 Furthermore, the role requires engagement across multiple software layers, including LLM applications, machine learning frameworks, and communication and computing libraries. The candidate will develop tools and methodologies using Machine Learning (ML) for comprehensive performance analysis and optimization, potentially incorporating learning-based agentic techniques. This work involves deep-diving across the software stack, from LLM applications and ML frameworks down to communication and computing libraries. This position offers a distinct opportunity to make significant contributions to the core infrastructure powering the next generation of large-scale AI systems.
 
 
 
 What You'll Be Doing
 
 
 
 <ul>
 <li>
 Design and implement resource allocation and combinatorial optimization techniques (e.g., reinforcement learning, LLM agents for DSE, Bayesian optimization and other multi-objective optimization techniques) to optimize LLM models at datacenter scale.
 </li>
 <li>
 Research, develop, and deploy AI/ML techniques to optimize large-scale Deep Learning (LLM) training and inference on NVIDIA supercomputers and distributed systems. This includes a focus on high-performance networking and NVIDIA communication libraries.
 </li>
 <li>
 Build and productionize ML-based tools for performance prediction and optimization, with a strong emphasis on networking aspects.
 </li>
 <li>
 Develop and deploy a scalable, reliable data curation pipeline capable of handling complex data types, such as time series and PyTorch model graphs, to effectively support the training of high-performance Machine Learning models.
 </li>
 <li>
 Collaborate across hardware and software teams to deliver valuable performance analysis insights.
 </li>
 <li>
 Lead performance test planning, establish performance targets for new technologies and solutions, and drive efforts to achieve those performance goals.
 
 
 </li>
 </ul>
 
 What We Need To See
 
 
 
 <ul>
 <li>
 Master's degree in Computer Science, Software Engineering, or equivalent experience.
 </li>
 <li>
 Experience applying machine learning techniques to computer architecture and system optimization problems. Desired experience involves leveraging ML at the intersection of at least two of the following areas: HPC, networking, and AI applications.
 </li>
 <li>
 Hands-on experience developing and deploying various learning algorithms (e.g., reinforcement learning, offline RL, supervised learning) to tackle optimization challenges within computer architecture, system design, or networking domains.
 </li>
 <li>
 Proficiency in building and using ML models with leading frameworks such as PyTorch or TensorFlow, or JAX.
 </li>
 <li>
 Proven ability to apply GNNs/transformers-based optimization to PyTorch model graph and Kineto execution traces.
 </li>
 <li>
 Expertise combining knowledge of NVIDIA GPUs, the CUDA library, and deep learning frameworks (TensorFlow/PyTorch) with networking concepts, including collective communication libraries (like NCCL) and protocols (such as RoCE and RDMA).
 </li>
 <li>
 Strong programming capabilities in Python, Bash, and C++.
 </li>
 <li>
 A collaborative teammate with effective communication and interpersonal abilities.
 
 
 </li>
 </ul>
 
 Ways To Stand Out From The Crowd
 
 
 
 <ul>
 <li>
 In-depth knowledge and experience with machine learning/reinforcement learning and frameworks.
 </li>
 <li>
 Comprehensive understanding of computer architecture, system architecture and networking.
 </li>
 <li>
 Extensive experience in applying machine learning techniques such as GNNs or related graph-based models.
 </li>
 <li>
 Knowledge in PyTorch, CUDA, and NCCL libraries.
 </li>
 <li>
 Proven software engineering/development skills
 
 
 </li>
 </ul>
 With competitive salaries and a comprehensive benefits package, NVIDIA is widely regarded as one of the most desirable technology employers in the world. Our teams are composed of some of the most forward‑thinking and driven engineers in the industry, and we continue to grow rapidly. If you are a senior data engineer passionate about building large‑scale, high‑impact data platforms, we&rsquo;d love to hear from you.
 
 
 Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 124,000 USD - 195,500 USD for Level 2, and 152,000 USD - 241,500 USD for Level 3.
 
 
 You will also be eligible for equity and benefits.
 
 
 Applications for this job will be accepted at least until April 28, 2026.
 
 
 This posting is for an existing vacancy.
 
 
 NVIDIA uses AI tools in its recruiting processes.
 
 
 NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
 
 
 , , JR2017100
 
 
</div>

Software Engineer, AI Networking- New College Grad 2026

We&rsquo;re starting to see the incredible potential of multimodal foundation and large language models, and many applications in the computer vision and machine learning domain that previously appeared infeasible are now within reach. We are looking for a highly motivated and skilled Machine Learning Integration Engineer to join our team in the Video Computer Vision group and help us enable that potential for realtime human understanding on Apple devices. The Video Computer Vision org has pioneered human-centric real-time features such as FaceID, FaceKit, and Gaze and Hand gesture control which have changed the way millions of users interact with their devices. We balance research and product requirements to deliver Apple quality, pioneering experiences, innovating through the full stack, and partnering with HW, SW and AI teams to shape Apple's products and bring our vision to life. 
 
Description 
 
As part of the Video Computer Vision (VCV) team, you will support our ML development and continuously improve our features. Working closely with ML algorithms engineers, data scientists and quality assurance teams, you&rsquo;ll help deploy state-of-the-art computer vision technologies on Apple devices, balancing performance with the compute and power constraints of on-device inference.&quot;,&quot;responsibilities&quot;:&quot;Develop applications and tools for algorithm evaluation, prototyping, and technology demonstrations. 
 
Support teams across Apple by integrating ML and CV components into production systems. 
 
On-device integration of CV/ML algorithms. 
 
Preferred Qualifications 
 
Experience with CoreFoundation, RealityKit and CoreML. 
 
Hands-on experience with CI/CD pipelines and practices. 
 
Experience with live camera streaming applications: Understanding of real-time video pipelines, image transformations, and rendering loops. 
 
Familiarity with common computer vision techniques (e.g., object detection, segmentation, tracking, pose estimation), sequence models for real-time inference and LLMs optimized for on-device performance. 
 
Minimum Qualifications 
 
Bachelor's degree in Computer Science or related discipline, and 2 years relevant industry experience. 
 
Strong foundational knowledge in Computer Science. 
 
Extensive programming experience in Python, Swift, C++. 
 
Experience working with PyTorch. 
 
Experience with machine learning model development lifecycle, including data preprocessing, model training, evaluation, and deployment. 
 
Foundational understanding of machine learning: ML algorithms and development pipelines, with the ability to work effectively with ML practitioners and integrate ML components into production systems. 
 
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.

On-Device Machine Learning Integration Engineer

<div>Apple is where individual imaginations come together, committing to the values that lead to great work. Every new product we build, service we create, or Apple Store experience we deliver is the result of us strengthening each other&rsquo;s ideas. That happens because every one of us believes that we can make something wonderful and share it with the world, changing lives for the better! Here, you&rsquo;ll do more than join something - you&rsquo;ll add something. 
 
The Information Intelligence team is redefining how billions of people use their devices to get information. We are an Applied ML team pushing the limits of question answering, assistant response ranking, and search technologies, while also responsible for a production service. We are part of a wider effort to power information across a variety of Apple products - including Siri, Spotlight, Safari, Messages, Lookup, and more. 
 
As part of our team, you will be leveraging and improving upon the latest deep learning techniques, such as LLM and RAG, in order to understand queries and user intents, rank documents, and find useful answers to users&rsquo; questions. Our team is responsible for training, fine-tuning and deploying these models at scale, using the latest advances for online inference optimization. 
 
As a Staff Machine Learning Engineer, you play a critical role in developing world-class Search and Q&amp;A experiences for Apple customers with cutting-edge search technologies and large language models. 
 
Description 
 
As a member of our fast-paced group, you&rsquo;ll have the unique and rewarding opportunity to shape upcoming products from Apple. Our team includes a diversity of backgrounds from applied scientists with a focus in NLP to experienced distributed systems engineers. As such, we are looking for candidates with in-depth understanding of machine learning fundamentals, applied machine learning experience, and strong software engineering skills. 
 
Our team is responsible for delivering next-generation Search and Question Answering systems across Apple products including Siri, Safari, Spotlight, and more. This is your chance to shape how people get information by leveraging your Search and applied machine learning expertise along with robust software engineering skills. You will collaborate with outstanding Search and AI engineers on large scale machine learning to improve Query Understanding, Retrieval, and Ranking, developing fundamental building blocks needed for AI powered experiences such as fine-tuning and reinforcement learning. This involves pushing the boundaries on document retrieval and ranking, developing sophisticated machine learning models, using embeddings and deep learning to understand the quality of matches. It also includes online learning to react quickly to change and natural language processing to understand queries. You will work with petabytes of data and combine information from multiple structured and unstructured sources to provide the best results and accurate answers to satisfy users' information-seeking needs.&quot;,&quot;responsibilities&quot;:&quot;Understanding product requirements then translating them into modeling and engineering tasks 
 
Analyzing search ranking and relevance requirements, issues, and opportunities 
 
Utilizing PyTorch, TensorFlow, or JAX for training and deploying deep learning models 
 
Building ML models for retrieval, relevance ranking, or query understanding 
 
Preferred Qualifications 
 
PhD in Computer Science, Artificial Intelligence, Machine Learning, Information Retrieval, Data Science or related field 
 
Strong industry background and experience in search and related technologies (LLMs, Machine Learning, NLP, Information Retrieval, Question Answering) 
 
Strong and validated experience of ML development and production systems 
 
Experience working with foundation models and LLMs 
 
Minimum Qualifications 
 
<ul><li>Understanding product requirements then translating them into modeling and engineering tasks</li></ul> 
<ul><li>Analyzing search ranking and relevance requirements, issues, and opportunities</li></ul> 
MS in Computer Science or related field 
 
10+ years of work experience in machine learning, deep learning or related field 
 
10+ years experience in shipping Search and Q&amp;A technologies and ML systems 
 
Excellent programming skills in mainstream programming languages such as C++, Python, Scala, and Go 
 
Experience delivering tooling and frameworks to evaluate individual components and end-to-end quality 
 
Strong analytical skills to systematically identify opportunities to improve search relevance and answer accuracy 
 
Strong written and verbal communication with the ability to articulate complex topics 
 
Excellent interpersonal skills and teamwork; demonstrated ability to connect and collaborate with others 
 
Passion for building phenomenal products and curiosity to learn 
 
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.</div>

Staff Machine Learning Engineer, Information Intelligence

Amazon.com

<div><h2 class="jobSectionHeader">DESCRIPTION</h2>
We are working on improving shopping on Amazon using the conversational capabilities of large language models and through customer behavioral data to make them more personalized for each customer. We are searching for pioneers who are passionate about technology, innovation, and customer experience, and are ready to make a lasting impact on the industry. In this role, you will be managing a team working on Large Language Model (LLM) and/or Vision-Language Model (VLM) post-training and alignment for new shopping experiences. You&rsquo;ll be working with talented scientists, engineers, and technical program managers (TPM) to innovate on behalf of our customers. If you&rsquo;re fired up about being part of a dynamic, driven team, then this is your moment to join us on this exciting journey!<h2 class="jobSectionHeader"> 
BASIC QUALIFICATIONS</h2><ul><li>3+ years of scientists or machine learning engineers management experience</li><li>Knowledge of ML, NLP, Information Retrieval and Analytics</li><li>PhD in Computer Science, Computer Engineering, or related technical field; OR Master's Degree in Computer Science, Computer Engineering, or related technical field with 5+ years of experience as a Scientist/Engineer.</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>Experience building machine learning models or developing algorithms for business application</li><li>Experience building complex software systems, especially involving deep learning, machine learning and computer vision, that have been successfully delivered to customers</li></ul> 
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. 
 
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company&rsquo;s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. 
 
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;t listed, please contact your Recruiting Partner. 
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life &amp; AD&amp;D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits. 
USA, CA, Palo Alto - 211,400.00 - 286,000.00 USD annually 
USA, WA, Seattle - 183,800.00 - 248,700.00 USD annually</div>

Applied Science Manager , Stores Foundation AI (SFAI)

Explore 695+ Aiml sr machine learning engineer data and ml innovation in Seattle this May. Find roles across top companies and apply now to boost your career.