aiml - applied ml engineer, data generation & verification

aiml - sr backend engineer, data and ml innovation

aiml - sr machine learning engineer, data and ml innovation

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

aiml - sr backend engineer, data and ml innovation Jobs in Seattle

aiml - sr machine learning engineer, data and ml innovation Jobs in Seattle

aws data engineer

data engineer, e-commerce Jobs in Seattle

data engineer, e-commerce

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

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

Wonder how Apple's Media Products show relevant search results and recommendations across Apple's media offerings - including App Store, Apple TV, Apple Music, Apple Podcasts, and Apple Books? Come join us! Design, build, and deploy machine learning pipelines that personalize the App Store for billions of users worldwide! Prototype, scale, and optimize algorithm improvements. Build robust, large-scale personalized recommender systems for Apps, Games, Videos, Podcasts and Fitness. See your work touch the lives of billions of Apple users worldwide. 
 
The Apple Services Engineering team is one of the most exciting examples of Apple&rsquo;s long-held passion for combining art and technology. We are the people who power the App Store, Apple TV, Apple Music, Apple Podcasts, and Apple Fitness+. And we do it on a massive scale, meeting Apple&rsquo;s high expectations with high performance, to deliver a huge variety of entertainment in over 35 languages to more than 150 countries. 
 
Our scientists and engineers build secure, end-to-end solutions powered by machine learning. Thanks to Apple&rsquo;s unique integration of hardware, software, and services, designers, scientists and engineers here partner to get behind a single unified vision. That vision always includes a deep commitment to strengthening Apple&rsquo;s privacy policy, one of Apple&rsquo;s core values. Although services are a bigger part of Apple&rsquo;s business than ever before, these teams remain small, flexible, and multi-functional, offering greater exposure to the array of opportunities here. 
 
Description 
 
We are looking for an exceptional Machine Learning Engineer to help us build and scale personalization systems using the latest advances in machine learning. With your engineering expertise, we want to develop robust, high-performance solutions to power personalized experiences across the App Store that enrich the lives of our customers. You will have the incredible opportunity to partner with researchers to see cutting-edge AI models deployed reliably at Apple&rsquo;s truly incredible global scale.&quot;,&quot;responsibilities&quot;:&quot;Design, build, and maintain scalable machine learning pipelines and infrastructure for training and serving personalization models. 
 
Partner closely with ML researchers to transition prototype models into highly optimized, production-ready systems. 
 
Optimize model inference for low latency and high throughput to meet the rigorous demands of Apple&rsquo;s global user base. 
 
Implement robust monitoring, A/B testing infrastructure, and evaluation frameworks to ensure model quality and reliability in production. 
 
Ship production-quality code and drive engineering best practices, system architecture, and code quality within the team. 
 
Preferred Qualifications 
 
Master&rsquo;s degree in Computer Science, Software Engineering, Mathematics, or a related field; OR equivalent practical industry experience. 
 
Industry experience specifically focused on MLOps, recommendation systems, or search ranking infrastructure. 
 
Minimum Qualifications 
 
Bachelor&rsquo;s degree in Computer Science, Software Engineering, Mathematics, or a related technical field. 
 
2+ years of relevant work experience. 
 
Strong software engineering fundamentals and technical competence in production-quality software development. 
 
Real-world experience with building, scaling, and deploying recommendation systems or large-scale ML models. 
 
Proven grasp of the open-source Python AI/ML tech stack, including PyTorch, scikit-learn, and numpy-scipy-pandas. 
 
Solid understanding of machine learning algorithms, design patterns, and tools, including deep learning and generative AI. 
 
Proficiency with big data technologies, data processing pipelines, and distributed computing (e.g., Spark, Hadoop, Kafka). 
 
Experience with ML infrastructure, model optimization, and serving models at scale with low latency. 
 
Strong written &amp; oral communication skills, with a collaborative mindset. 
 
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, Apple Services Engineering

MORSE Corp

<div>
 
 MORSE Corp is an employee owned, small business based in Cambridge, MA, Arlington, VA, and Seattle, WA with a history of fielding
 
 cutting-edge
 
 
 technology. MORSE boasts a specially selected team of scientists, engineers, and software developers to deliver best-in-class technical solutions that solve difficult multidisciplinary problems faced by the US National Security Ecosystem.
 
 
 &nbsp;
 
 
 
 
 We are seeking a Machine Learning Engineer to join our team at MORSE.  You will play a pivotal role in designing, implementing, and managing complex ML algorithms and systems, with a focus on computer vision (CV) and other types of data. You will be responsible for acquiring truth data, integrating algorithms, testing algorithms, combining algorithms, reviewing literature to stay on top of the latest-and-greatest methods, analyzing data from field tests, and developing advanced algorithms.  MORSE&rsquo;s AI &amp; ML work crosses modalities, and experience or interest in the fields of Large Language Models (LLM), audio analysis, computer vision, and advanced reasoning is a plus. You will work with MORSE&rsquo;s current team of engineers to transition algorithms to production, which may run on on-prem servers, on the cloud, or on a real-time embedded system. You will be part of our team working to accelerate our US National Security customers abilities to use natural language processing capabilities in mission-critical environments.
 
 
 &nbsp;
 
 
 
 Responsibilities:
 
 
 &nbsp;
 
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 <li>
 
 Develop, fine-tune, train, and optimize Computer Vision algorithms processing tasks such as object detection and tracking.&nbsp;
 
 
 &nbsp;
 
 </li>
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 Use MLOps tools for efficient experiment tracking, data management, and reproducibility
 
 
 &nbsp;
 
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 Write robust, efficient, and maintainable code
 
 
 &nbsp;
 
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 Track the latest advancements with machine learning research to bring new techniques and methodologies to MORSE
 
 
 &nbsp;
 
 </li>
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 Conduct experiments and perform rigorous evaluations to assess the effectiveness and efficiency of CV models
 
 
 &nbsp;
 
 
 </li>
 </ul>
 
 Skills and Requirements:
 
 
 &nbsp;
 
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 <li>
 
 US CITIZENSHIP REQUIRED and the ability to obtain a U.S. Security Clearance
 
 
 &nbsp;
 
 </li>
 </ul>
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 <li>
 
 Masters or Ph.D. in Computer Science, Computer Engineering, Data Science, Aerospace, Mathematics, Physics, or related field
 
 
 &nbsp;
 
 </li>
 </ul>
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 Proven experience in applying CV models, techniques, frameworks, and libraries to implement and fine-tune models
 
 
 &nbsp;
 
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 Proven experience testing and validating the performance of AI technologies in real-world applications
 
 
 &nbsp;
 
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 Proficiency in Python
 
 
 &nbsp;
 
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 Experience with cloud platforms (AWS and Azure)
 
 
 &nbsp;
 
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 Experience with Docker
 
 
 &nbsp;
 
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 Experience with MLOps tools such as Airflow, MLFlow, AimStack, etc.
 
 
 &nbsp;
 
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 Exceptional communication skills and the ability to work well with customers
 
 
 &nbsp;
 
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 Understanding of Department of Defense requirements and standards is a plus
 
 
 &nbsp;
 
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 </ul>
 
 
 &nbsp;
 
 
 
 
 
 
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 &nbsp;
 
 
 
 MORSE Corp&rsquo;s salary range for this role carefully considers a wide range of compensation factors, including but not limited to, prior experience, education, skills and expertise, location, internal equity, and other factors that are job related and consistent with business need. Therefore, final offer amounts may vary from the amount stated. Depending on role eligibility, total compensation may also include bonus, stock, 401(k) match, paid time off, medical, dental, vision and life insurance.Employees also receive 10 paid holidays per year. MORSE maintains an &ldquo;open&rdquo; leave policy that does not restrict exempt, regular full-time employees to a specific&nbsp;number of paid sick or vacation days. However, this policy is not an &ldquo;unlimited&rdquo; paid leave policy.&nbsp;
 
 
 Compensation: $90,000 USD - $210,000 USD
 
 
 The team at MORSE takes pride in being the smart team that is easy to work with. We focus on steady, long-term success with an emphasis on exceptionalism and delivering mission-critical impact to our customers. For more information, please visit www.morsecorp.com.
 
 
 
 &nbsp;
 
 
</div>

Machine Learning Engineer

Amazon

<div>
 
 Description
 
 
 
 Are you passionate about solving unique customer-facing problems in the Amazon scale? Are you excited about utilizing statistical analysis, machine learning, data mining and leverage tons of Amazon data to learn and infer customer shopping patterns? Do you enjoy working with a diversity of engineers, machine learning scientists, product managers and user-experience designers? If so, you have found the right match!
 
 
 Fashion is extremely fast-moving, visual, subjective, and it presents numerous unique problem domains such as product recommendations, product discovery and evaluation. The vision for Amazon Fashion is to make Amazon the number one online shopping destination for Fashion customers by providing large selections, inspiring and accurate recommendations and customer experience.
 
 
 The NAS Shop and Keep (SHAKE) organization empowers customers to make confident, lasting purchase decisions by minimizing purchase anxiety and reducing returns. The NAS SHAKE science team advances this mission by innovating and developing scalable ML solutions tailored to these unique challenges. The team is hiring a Data Scientist who has a solid background in Statistical Analysis, Machine Learning and Data Mining and a proven record of effectively analyzing large complex heterogeneous datasets, and is motivated to grow professionally as a Data Scientist.
 
 
 Key job responsibilities
 
 
 <ul>
 <li>
 You will work on our Science team and partner closely with applied scientists, data engineers as well as product managers, UX designers, and business partners to answer complex problems via data analysis. Outputs from your analysis will directly help improve the performance of the ML based recommendation systems thereby enhancing the customer experience as well as inform the roadmap for science and the product.
 </li>
 <li>
 You can effectively analyze complex and disparate datasets collected from diverse sources to derive key insights, build segmentation models and improve customer experience by reducing retail returns.
 </li>
 <li>
 You have excellent communication skills to be able to work with cross-functional team members to understand key questions and earn the trust of senior leaders.
 </li>
 <li>
 You are able to multi-task between different tasks such as gap analysis of algorithm results, integrating multiple disparate datasets, doing business intelligence, analyzing engagement metrics or presenting to stakeholders.
 </li>
 <li>
 You thrive in an agile and fast-paced environment on highly visible projects and initiatives.
 
 
 </li>
 </ul>
 
 Basic Qualifications
 
 
 
 <ul>
 <li>
 1+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
 </li>
 <li>
 2+ years of data/research scientist, statistician or quantitative analyst in an internet-based company with complex and big data sources experience
 </li>
 <li>
 1+ years of creating or contributing to mathematical textbooks, research papers, or educational content experience
 </li>
 <li>
 Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)
 
 
 </li>
 </ul>
 
 Preferred Qualifications
 
 
 
 <ul>
 <li>
 Ph.D. in Science, Technology, Engineering, or Mathematics (STEM)
 </li>
 <li>
 Knowledge of statistical packages and business intelligence tools such as SPSS, SAS, S-PLUS, or R
 </li>
 <li>
 Knowledge of machine learning concepts and their application to reasoning and problem-solving
 </li>
 <li>
 Experience with clustered data processing (e.g., Hadoop, Spark, Map-reduce, and Hive)
 </li>
 <li>
 Experience applying quantitative analysis to solve business problems and making data-driven business decisions
 </li>
 <li>
 Usage of generative AI tools to enhance workflow efficiency, with a willingness to learn effective prompting and evaluation practices.
 </li>
 <li>
 Ability to recognize opportunities where generative AI could enhance products, workflows, or customer experiences.
 
 
 </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.
 
 
 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, WA, Seattle - 108,300.00 - 160,000.00 USD annually
 
 
 
 
 Company
 
 - Amazon.com Services LLC
 
 
 Job ID: A3206663
</div>

Data Scientist I, SHAKE

DigitalOcean

<div><div>Dive in and do the best work of your career at DigitalOcean. Journey alongside a strong community of top talent who are relentless in their drive to build the simplest scalable cloud. If you have a growth mindset, naturally like to think big and bold, and are energized by the fast-paced environment of a true industry disruptor, you'll find your place here. We value winning together&mdash;while learning, having fun, and making a profound difference for the dreamers and builders in the world.</div><h2 class="jobSectionHeader">
We are looking for a Manager, Customer Success Engineering (AI &amp; Cloud Support) who is passionate about delivering exceptional support experiences and building high-performing teams.</h2>

As a Manager, CSE (AI &amp; Cloud Support) at DigitalOcean, you will operate as a Support Manager leading a team of Customer Success Engineers (CSEs) supporting strategic customers across cloud infrastructure and emerging AI/ML workloads. Reporting to the Senior Manager of Customer Success Engineering, you will own day-to-day support operations, team performance, and customer experience outcomes.

This role is focused on driving operational excellence while building strong technical depth within the team across AI, GPUs, Kubernetes, Databases and core cloud offerings. You will play a key role in ensuring consistent support coverage, developing SMEs, and partnering cross-functionally with Product and Engineering to improve both customer experience and product quality.

The ideal candidate brings a deep understanding of cloud and AI/ML ecosystems, including machine learning operations (MLOps), and enterprise support, combined with a passion for innovation and automation, and a proven ability to lead teams in delivering &quot;white-glove&quot; experiences for strategic customers.<h2 class="jobSectionHeader"> 

What You'll Do:</h2>

Team Leadership &amp; Development
<ul>
<li>Lead, hire, train, mentor and develop a high-performing team of Customer Success Engineers (CSEs), driving accountability, performance, and career growth</li>
<li>Establish performance metrics (KPIs/SLAs) and conduct regular 1:1s, performance reviews, and career development planning.</li>
<li>Own end-to-end support operations, including queue management, escalations, and shift planning to ensure consistent 24x7 coverage.</li>
<li>Drive improvements in key support metrics such as CSAT, response times, resolution times, and overall support quality.</li>
<li>Build and strengthen technical expertise within the team across core areas such as Kubernetes (DOKS), Databases, Compute, and AI/ML workloads.</li> 
</ul>
Strategic Customer Support 
<ul>
<li>Act as the ultimate point of technical escalation for our largest, most strategic enterprise customers across Cloud and AI/ML workloads, stepping in to manage critical incidents and high-severity (Sev1/Sev2) issues.</li>
<li>Design and implement customized support plans, SLAs, and escalation pathways tailored to the needs of strategic accounts.</li>
<li>Partner closely with Technical Account Managers (TAMs), Growth Account Managers (GAM) to conduct Executive Business Reviews (EBRs) and ensure customers are maximizing the value of our Cloud and AI/ML products.</li>
<li>Proactively identify risks and opportunities within strategic accounts to improve customer experience, adoption, and retention.</li>
</ul>
Technical &amp; Cross-Functional Operations
<ul>
<li>Serve as the Voice of the Customer (VoC) to Product and Engineering teams, synthesizing support data to advocate for bug fixes, feature requests, and UX improvements.</li>
<li>Own and continuously improve escalation protocols between AI/ML Support and CloudOps, Infrastructure Engineering, and Product &mdash; including Jira escalation routing, Sev1 bridge management, and post-incident documentation.</li>
<li> Own the development and maintenance of SOPs, escalation runbooks, HVC support playbooks, and knowledge base content &mdash; treating documentation infrastructure as a core operational lever for team scalability.</li>
<li>Contribute to the vision for AI and automation within support&mdash;building intelligent tooling and driving the team toward an automation-first model to improve efficiency, scalability, and customer experience.</li>
<li>Foster a culture of continuous learning, ensuring the team stays ahead of evolving cloud technologies, AI/ML frameworks, and industry trends.</li>
</ul><h3 class="jobSectionHeader">Key Metrics:</h3>
<ul><li>Customer Satisfaction (CSAT) for strategic accounts</li>
<li>Time to Response and Resolution (TTR) for strategic customers</li>
<li>Tier 1 resolution rate vs. escalation rate</li>
<li>Time-to-escalation and engineering handoff SLA adherence</li>
<li>SLA adherence and escalation response times</li>
<li>Support productivity and quality (QA scores)</li>
<li>Post-incident documentation completion rate</li>
</ul><h2 class="jobSectionHeader">What You'll Add to DigitalOcean:</h2>
<ul><li>Experience: 5+ years of experience in Technical Support, Customer Success, or Technical Account Management within B2B SaaS, Cloud, or AI/ML environments ideally including experience supporting AI-native, high-growth companies with 24x7 production dependencies on GPU infrastructure.</li>
<li>Leadership: 2+ years of people management experience leading technical, customer-facing teams, preferably in a high-growth, post-acquisition, or rapidly scaling environment.</li>
<li>Technical Domain Expertise: Solid understanding of AI/ML concepts, including Generative AI, Large Language Models (LLMs), natural language processing (NLP), and MLOps. Deep familiarity with GPU infrastructure (NVIDIA H100/H200, bare metal GPU provisioning) and AI inference workloads is strongly preferred.</li>
<li>Coding/Integration: Proficiency in reading and debugging code (Python preferred) and troubleshooting RESTful APIs and cloud architecture.</li>
<li>Communication: Excellent verbal and written communication skills, with the ability to translate complex technical or AI concepts for diverse audiences OR to both highly technical engineers and non-technical business executives.</li>
<li>Problem-Solving: Proven ability to remain calm under pressure and de-escalate high-stakes situations with enterprise clients.</li>
</ul>
Preferred Qualifications:
<ul>
<li>Hands-on experience with ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and AI toolchains (e.g., LangChain, Hugging Face).</li>
<li>Experience with major cloud platforms (AWS, Google Cloud, Azure) and their native AI/ML services.</li>
<li>Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related technical field.</li>
<li>ITIL or equivalent service management certification</li>
</ul><h2 class="jobSectionHeader">Compensation Range:</h2>
<ul><li>$125,000 - $153,000</li>
</ul>
<ul><li>This is a remote role</li></ul>

JR: 2026-7692

#LI-Remote<div><h2 class="jobSectionHeader">
Why You'll Like Working for DigitalOcean</h2>
<ul><li>We innovate with purpose. You'll be a part of a cutting-edge technology company with an upward trajectory, who are proud to simplify cloud and AI so builders can spend more time creating software that changes the world. As a member of the team, you will be a Shark who thinks big, bold, and scrappy, like an owner with a bias for action and a powerful sense of responsibility for customers, products, employees, and decisions.</li>
<li>We prioritize career development. At DO, you'll do the best work of your career. You will work with some of the smartest and most interesting people in the industry. We are a high-performance organization that will always challenge you to think big. Our organizational development team will provide you with resources to ensure you keep growing. We provide employees with reimbursement for relevant conferences, training, and education. All employees have access to LinkedIn Learning's 10,000+ courses to support their continued growth and development.</li>
<li>We care about your well-being. Regardless of your location, we will provide you with a competitive array of benefits to support you from our Employee Assistance Program to Local Employee Meetups to flexible time off policy, to name a few. While the philosophy around our benefits is the same worldwide, specific benefits may vary based on local regulations and preferences.</li>
<li>We reward our employees. The salary range for this position is based on market data, relevant years of experience, and skills. You may qualify for a bonus in addition to base salary; bonus amounts are determined based on company and individual performance. We also provide equity compensation to eligible employees, including equity grants upon hire and the option to participate in our Employee Stock Purchase Program.</li>
<li>DigitalOcean is an equal-opportunity employer. We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service.</li>
</ul>
Application Limit: You may apply to a maximum of 3 positions within any 180-day period. This policy promotes better role-candidate matching and encourages thoughtful applications where your qualifications align most strongly.</div></div>

Manager, Customer Success Engineering

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