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kubernetes development engineer

Capgemini

<div><div><div><p>Seattle</p><div>
Kubernetes Development Engineer</div><p>
</p></div></div><p></p><div><div><div><div><div><p>
At Capgemini Engineering, the world leader in engineering services, we bring together a global team of engineers, scientists, and architects to help the world&rsquo;s most innovative companies unleash their potential. From autonomous cars to life-saving robots, our digital and software technology experts think outside the box as they provide unique R&amp;D and engineering services across all industries. Join us for a career full of opportunities. Where you can make a difference. Where no two days are the same.</p><div><div><div><div>
Location</div></div><div><p>
This is a fully remote role.</p></div></div><div><div><div>
About the job you&rsquo;re considering</div></div><div><p>
We are seeking a Kubernetes Engineer to design, deploy, and operate Kubernetes-based hosting platforms across edge and embedded systems. You&rsquo;ll play a critical role in ensuring our platform is secure, scalable, and resilient&mdash;supporting multi-tenant services and orchestrating workloads across aircraft and ground-based environments. This is a high-impact role for engineers who thrive in cloud-native ecosystems and are passionate about automation, security, and performance optimization. Experience in the telecom domain and networking is a strong plus.</p></div></div><div><div><div>
Your role</div></div><div><ul><li>
Develop and maintain custom Kubernetes controllers, CRDs, and operators to extend platform capabilities.</li><li>
Integrate Kubernetes with Linux-based infrastructure bootstrapped via PXE, OTA, and other provisioning methods.</li><li>
Deploy and configure K3s clusters across heterogeneous hardware (bare metal, ARM/x86 nodes, and accelerators).</li><li>
Automate cluster provisioning, node registration, and upgrade workflows.</li><li>
Monitor platform health using Prometheus, Grafana, and Kubernetes Events.</li><li>
Enforce network policies, RBAC, secrets management, and container security best practices.</li><li>
Optimize Kubernetes performance on constrained hardware and air-gapped systems.</li><li>
Troubleshoot container runtimes, DNS resolution, and overlay networking (e.g., Calico, Flannel).</li></ul></div></div><div><div><div>
Your skills and experience</div></div><div><ul><li>
5+ years of experience managing Kubernetes platform components and lifecycle operations.</li><li>
Understanding of multi-node hybrid clusters across x86, ARM, and accelerators.</li><li>
Proficiency with Helm charts and Argo CD for application and platform deployment.</li><li>
Strong skills in Go, Bash scripting, YAML/JSON configuration, and REST API development.</li><li>
Deep understanding of Kubernetes CNI plugins and network policy management.</li></ul></div></div></div><p>
The base compensation range for this role in the posted location is: $76,200-$187,740.</p><p>
Capgemini provides compensation range information in accordance with applicable national, state, provincial, and local pay transparency laws. The base compensation range listed for this position reflects the minimum and maximum target compensation Capgemini, in good faith, believes it may pay for the role at the time of this posting. This range may be subject to change as permitted by law.</p><p>
The actual compensation offered to any candidate may fall outside of the posted range and will be determined based on multiple factors legally permitted in the applicable jurisdiction.</p><p>
These may include, but are not limited to: Geographic location, Education and qualifications, Certifications and licenses, Relevant experience and skills, Seniority and performance, Market and business consideration, Internal pay equity.</p><p>
It is not typical for candidates to be hired at or near the top of the posted compensation range.</p><p>
In addition to base salary, this role may be eligible for additional compensation such as variable incentives, bonuses, or commissions, depending on the position and applicable laws.</p><p>
</p><p>Capgemini offers a comprehensive, non-negotiable benefits package to all regular, full-time employees. In the U.S. and Canada, available benefits are determined by local policy and eligibility and may include:
</p><ul><li>Paid time off based on employee grade (A-F), defined by policy: Vacation: 12-25 days, depending on grade, Company paid holidays, Personal Days, Sick Leave</li></ul><ul><li>
Medical, dental, and vision coverage (or provincial healthcare coordination in Canada)</li><li>
Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada)</li><li>
Life and disability insurance</li><li>
Employee assistance programs</li><li>
Other benefits as provided by local policy and eligibility</li></ul><p>
Important Notice: Compensation (including bonuses, commissions, or other forms of incentive pay) is not considered earned, vested, or payable until it becomes due under the terms of applicable plans or agreements and is subject to Capgemini&rsquo;s discretion, consistent with applicable laws. The Company reserves the right to amend or withdraw compensation programs at any time, within the limits of applicable legislation.</p><p>
</p><p>Disclaimers</p><p>
Capgemini is an Equal Opportunity Employer encouraging inclusion in the workplace. Capgemini also participates in the Partnership Accreditation in Indigenous Relations (PAIR) program which supports meaningful engagement with Indigenous communities across Canada by promoting fairness, accessibility, inclusion and respect. We value the rich cultural heritage and contributions of Indigenous Peoples and actively work to create a welcoming and respectful environment. All qualified applicants will receive consideration for employment without regard to race, national origin, gender identity/expression, age, religion, disability, sexual orientation, genetics, veteran status, marital status or any other characteristic protected by law.</p><p>
This is a general description of the Duties, Responsibilities and Qualifications required for this position. Physical, mental, sensory or environmental demands may be referenced in an attempt to communicate the manner in which this position traditionally is performed. Whenever necessary to provide individuals with disabilities an equal employment opportunity, Capgemini will consider reasonable accommodations that might involve varying job requirements and/or changing the way this job is performed, provided that such accommodation does not pose an undue hardship. Capgemini is committed to providing reasonable accommodation during our recruitment process. If you need assistance or accommodation, please reach out to your recruiting contact.</p><p>
Please be aware that Capgemini may capture your image (video or screenshot) during the interview process and that image may be used for verification, including during the hiring and onboarding process.</p><p></p><p><br>
</p><p>Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, generative AI, cloud and data, combined with its deep industry expertise and partner ecosystem.</p><p>
</p></div></div><div><div><div><div><div>Ref. code</div><div>
436453-en_GB</div></div><div><div>
Posted on</div><div>
12 Mar 2026</div></div><div><div>
Experience level</div><div>
Experienced Professionals</div></div><div><div>
Contract type</div><div>
Permanent</div></div><div><div>
Location</div><div>
Seattle</div></div><div><div>
Business unit</div><div>
Engineering and RandD Services</div></div><div><div>
Brand</div><div>
Capgemini Engineering</div></div><div><div>
Professional communities</div><div>
Products &amp; Systems Engineering</div></div></div></div></div></div></div></div></div><p></p>

Kubernetes Development Engineer

NVIDIA

<div><div>Are you passionate about Kubernetes and AI and want to help build the best platform for ML/AI infrastructure? Do you thrive when your work directly empowers teams to push the boundaries of what's possible?</div><div></div><div>
We're the Platform API team within NVIDIA's DGX Cloud organization - a collaborative group of cloud platform engineers, architects, and SREs who are passionate about building and nurturing the declarative, Kubernetes-native control plane that powers GPU-accelerated infrastructure across multiple cloud providers. Together, we're empowering the world's leading AI teams to train and deploy at datacenter scale. We design and extend Kube-like APIs, and we craft Go-based reconciliation controllers that thoughtfully turn high-level intent into production-ready AI infrastructure. We take pride in owning our code end-to-end, and we care deeply about the full lifecycle of multi-cloud GPU clusters, from customer onboarding and provisioning through upgrades and decommissioning. We partner closely with our runtime, cloud architecture, observability, and storage teams to solve sophisticated distributed systems challenges together. As a team, we're strengthening NVIDIA's approach to Cloud Native development.</div><div></div><div>
What you will be doing:</div><ul><li><div>
Develop software systems to support large scale deployments of cloud infrastructure</div></li><li><div>
Design and develop APIs to support Infrastructure as Code (IaC) automation and deployment workflows.</div></li><li><div>
Responsible for contributing to multiple source code projects to fulfill NVIDIA requirements with software services</div></li><li><div>
Work and collaborate with engineering managers, architects, designers, and frontend engineers to deliver high quality software</div></li><li><div>
Automate the validation of software solutions with unit and integration tests</div></li><li><div>
Participate in the ownership and health of CI/CD pipelines from dev to production environments</div></li><li><div>
Collaborate with other specialists for feedback on proposed designs and product direction</div></li><li><div>
Openly share successes and failures in a no blame environment</div></li></ul><div></div><div>
What we need to see:</div><ul><li><div>
BS in Computer Science, Information Systems, Computer Engineering or equivalent experience</div></li><li><div>
6+ years of proven experience in large scale software development</div></li><li><div>
Experience building and shipping services on Kubernetes</div></li><li><div>
Background with using and chipping in to open-source projects</div></li><li><div>
Collaborated with teams to write software to support cloud services at scale</div></li><li><div>
Programming experience in a relevant language, e.g. Golang, Python</div></li><li><div>
Communicate design and quality strategy in written, visual, and oral formats</div></li><li><div>
Experience with a wide range of modern infrastructure tools and technologies</div></li></ul><div></div><div>
Ways to stand out from the crowd:</div><ul><li><div>
Experience with Kubernetes Cluster API, Terraform, Tinkerbell, and other infrastructure tooling</div></li><li><div>
Practical experience with Azure, GCP, or AWS</div></li><li><div>
Capable of refactoring software to run in systems such as Kubernetes</div></li><li><div>
Ability to discuss and work with CSI, CNI, and CRI and/or familiarity with the CNCF and the tooling across the ecosystem</div></li><li><div>
Upstream contribution in open source projects</div></li></ul><div></div><div>
NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High-Performance Computing and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services. Our work opens up new universes to explore, enables amazing creativity and discovery, and powers what were once science fiction inventions from artificial intelligence to autonomous cars. NVIDIA is looking for great people like you to help us accelerate the next wave of artificial intelligence. NVIDIA is widely considered to be one of the technology world&rsquo;s most desirable employers. We have some of the most forward-thinking and hardworking people on the planet working for us. If you're a creative, curious, and driven technical leader, we want to hear from you!</div><div></div>
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD.<div></div><div><div><div><div><div><div><div><div>
You will also be eligible for equity and <div>benefits</div>.</div></div></div></div></div></div></div></div><div></div>
Applications for this job will be accepted at least until March 16, 2026.<div></div><div>
This posting is for an existing vacancy.</div><div>
NVIDIA uses AI tools in its recruiting processes.</div><div></div>
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.</div><div></div>

Cloud Platform Software Engineer

OpenAI

<div>
 <strong>
  About The Team
  <br/>
  <br/>
 </strong>
 We bring OpenAI's technology to the world through products like ChatGPT and the OpenAI API. Our customers build fast-growing businesses around our APIs, which power products that were never before possible. We simultaneously ensure that our powerful tools are used responsibly. Safe deployment is more important to us than unfettered growth.
 <br/>
 <br/>
 The Engineering team manages a massive fleet of GPUs with scalable, robust infrastructure powered by Kubernetes, Go, Python, Terraform, Kafka, Postgres, and Snowflake.
 <br/>
 <br/>
 <strong>
  About The Role
  <br/>
  <br/>
 </strong>
 We&rsquo;re looking for experienced and creative engineers to help us scale our existing systems and build the next-generation system to enable a whole new class of products. We are seeking an engineer who is comfortable with full-stack development and has experience with Real-Time Communication (RTC). Candidates should have experience with scaled real-time communication systems in production.
 <br/>
 <br/>
 <strong>
  Responsibilities
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Design and build development and production platforms that power our systems.
  </li>
  <li>
   Partner with researchers, engineers, product managers, and designers to bring new features and research capabilities to the world.
  </li>
  <li>
   Accelerate engineering productivity by empowering your fellow engineers with excellent tooling and systems.
  </li>
  <li>
   Build and provide operational support for globally deployed systems, powering some of the most advanced products in the market. This includes participating in an on-call rotation to respond to critical incidents as needed.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  You Might Thrive In This Role If You
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Have significant experience building (and rebuilding) production systems to deliver new product capabilities and handle increasing scale.
  </li>
  <li>
   Have experience with real-time communication products and systems, including audio and video calling, WebRTC or competing protocols, encoding/decoding, signaling, lip sync, etc.
  </li>
  <li>
   Care deeply about user experience and take pride in building products that solve customer needs.
  </li>
  <li>
   Have a humble attitude, eagerness to help colleagues, and a willingness to do whatever it takes to make the team succeed.
  </li>
  <li>
   Own problems end-to-end and are willing to pick up any necessary knowledge to get the job done.
  </li>
  <li>
   Have been a startup founder or an early-stage engineer.
  </li>
  <li>
   Experience in Machine Learning techniques is a plus but not required.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  About OpenAI
  <br/>
  <br/>
 </strong>
 OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.
 <br/>
 <br/>
 We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.
 <br/>
 <br/>
 For additional information, please see OpenAI&rsquo;s Affirmative Action and Equal Employment Opportunity Policy Statement.
 <br/>
 <br/>
 Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.
 <br/>
 <br/>
 To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance.
 <br/>
 <br/>
 We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.
 <br/>
 <br/>
 OpenAI Global Applicant Privacy Policy
 <br/>
 <br/>
 At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.
</div>


Software Engineer, Real Time

Apple

<p>The Apple Ray team is seeking a Senior / Staff Software Engineer with strong distributed systems expertise and a solid background in machine learning. In this hybrid role, you will design and build core components of Apple&rsquo;s unified data+ML platform powered by open-source Ray, while also partnering with ML teams to ensure the platform meets the needs of large-scale training and inference workloads.<br>
<br>
You will contribute to the distributed runtime, orchestration layer, and system APIs that power Apple&rsquo;s intelligent features across products and services. This role is ideal for a software engineer who enjoys low-level systems work but is also fluent in ML workflows and models at scale.<br>
<br>
<b>Description</b><br>
<br>
Apple Ray integrates deeply with Apple&rsquo;s data and ML ecosystem to provide a unified platform for building, orchestrating, and scaling complex ML and data pipelines. As a Software Engineer with ML background, you will design distributed systems that support large-scale model training, tuning, and inference across heterogeneous compute environments-from bare-metal GPU clusters to cloud-native infrastructure.<br>
<br>
You will build features that enhance developer productivity for ML engineers, improve resource efficiency, and advance the performance and reliability of Apple&rsquo;s ML workloads. You&rsquo;ll collaborate closely with ML practitioners to translate model and pipeline needs into robust platform capabilities, while also improving the underlying distributed runtime and control plane.<br>
<br>
This role requires strong engineering fundamentals, hands-on experience with ML systems, and a passion for building scalable infrastructure.&quot;,&quot;responsibilities&quot;:&quot;Build scalable distributed systems and platform components using Ray that power Apple&rsquo;s data+ML workflows.<br>
<br>
Develop APIs, libraries, and services that improve the efficiency and usability of large-scale ML training and inference pipelines.<br>
<br>
Optimize performance and resource utilization across GPU/CPU clusters for ML workloads running at Apple scale.<br>
<br>
Collaborate with ML teams to understand model and pipeline needs and translate them into robust platform features.<br>
<br>
Design fault-tolerant orchestration mechanisms, autoscaling strategies, and runtime improvements for distributed ML jobs.<br>
<br>
Diagnose complex issues across distributed systems and ML pipelines to ensure reliability and availability.<br>
<br>
Improve observability, monitoring, and debugging capabilities targeted at ML-centric distributed workloads.<br>
<br>
Contribute to architectural decisions and, where appropriate, upstream enhancements to Ray and related tools.<br>
<br>
<b>Preferred Qualifications</b><br>
<br>
Experience with distributed training frameworks (DeepSpeed, Horovod, FSDP, ZeRO).<br>
<br>
Background in optimizing GPU workloads or performance benchmarking.<br>
<br>
Experience with model orchestration systems or ML platforms.<br>
<br>
Contributions to open-source ML or distributed systems projects.<br>
<br>
Familiarity with large-scale data systems such as Spark, Flink, or similar.<br>
<br>
<b>Minimum Qualifications</b><br>
<br>
6+ years building distributed systems, high-scale backend services, or compute runtimes.<br>
<br>
Solid background in ML workflows, model training, model serving, or data pipeline development.<br>
<br>
Proficiency in Python, plus strong experience in a systems-level language (C++, Rust, Go, or Java).<br>
<br>
Experience with ML frameworks such as PyTorch or TensorFlow and familiarity with GPU-based training.<br>
<br>
Understanding of parallelism strategies, model scaling, or distributed training concepts.<br>
<br>
Experience with cluster orchestration (Kubernetes, EKS, GKE) or large-scale compute systems.<br>
<br>
Strong debugging skills across distributed and ML-centric runtime environments.<br>
<br>
Ability to work cross-functionally with ML engineers, data engineers, and infrastructure teams.<br>
<br>
B.S., M.S., or Ph.D. in Computer Science, Machine Learning, or related technical fields - or comparable software engineering experience.<br>
<br>
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 .<br>
<br>
<b>Pay &amp; Benefits</b><br>
<br>
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.<br>
<br>
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.<br>
<br>
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.</p>

Senior / Staff ML Engineer, Apple Ray, Apple Data Platform

<p>As a Data Engineer on the Capacity Engineering team, you will help design, build, and operate the data foundation that drives capacity, cost, and power-related decisions across Apple&rsquo;s infrastructure footprint.<br>
<br>
In this role, you will:<br>
<br>
Architect, implement, and maintain large-scale batch and streaming pipelines that ingest, process, and model infrastructure telemetry, cost, metering, utilization, forecasting, and power metrics from multiple clouds and bare metal environments.<br>
<br>
Design and evolve robust data models (with a strong focus on dimensional modeling) and storage patterns that support analytics, internal billing, and efficiency use-cases.<br>
<br>
Treat data as a product: define quality checks, SLAs, and observability to ensure data is accurate, timely, and trusted by stakeholders across Apple.<br>
<br>
Integrate and enrich raw signals with metadata and attribution to power use cases such as internal billing/showback, usage understanding, efficiency and optimization, clawbacks, planning, and procurement.<br>
<br>
Collaborate closely with data scientists, software engineers, platform teams, finance partners, program managers, and leadership to translate requirements into scalable, reliable data solutions and services.<br>
<br>
Implement standard methodologies for data governance, lineage, metadata management, and security, in alignment with Apple&rsquo;s standards for data protection and privacy.<br>
<br>
Build end-to-end data solutions that include logging, anomaly detection, data validation, cleaning, and transformation, with strong emphasis on monitoring, debuggability, and continuous improvement.<br>
<br>
Contribute to the evolution of our data and platform stack, including tooling, frameworks, and standards for development, testing, deployment, and operations (CI/CD, infrastructure as code, etc.).<br>
<br>
<b>Description</b><br>
<br>
Apple&rsquo;s Capacity data engineering team, within the Apple Services Engineering organization, is building the centralized data backbone that powers how Apple understands, plans, and optimizes its cloud and data center infrastructure.<br>
<br>
We engineer a unified, trusted data lake that consolidates cost, metering, utilization, forecasting, and power metrics produced by Apple platforms and systems (including bare metal) across both third-party and Apple internal clouds. Enriched with metadata and attribution, this becomes the single source of truth for internal billing, understanding usage and utilization, clawbacks, planning, procurement, and efficiency initiatives.<br>
<br>
We collaborate with platform engineering, finance, capacity engineering, and leadership teams to build large-scale data pipelines, enable descriptive and predictive analytics, and power dashboards and products that support critical business decisions. This is your opportunity to help design and operate highly visible, global-scale systems processing petabytes of data and supporting hundreds of users across Apple.<br>
<br>
Come join us to help deliver the next generation of infrastructure insights at Apple.<br>
<br>
<b>Preferred Qualifications</b><br>
<br>
Advanced degree in a related field a plus.<br>
<br>
Experience with data visualization / BI tools, such as Superset or Tableau (other tools like QuickSight, QlikView, Cognos, or Business Objects are a plus)<br>
<br>
Experience with containerization and orchestration, such as Docker and Kubernetes/EKS is a plus<br>
<br>
Understanding of authentication and authorization (AuthN/AuthZ) patterns<br>
<br>
Knowledge of data governance principles, data security best practices, and data privacy regulations<br>
<br>
<b>Minimum Qualifications</b><br>
<br>
Bachelors degree or equivalent experience in Computer Science, Information systems, Software Engineering, Data Science or related field.<br>
<br>
5+ years of experience in data engineering (or equivalent practical experience), including:<br>
<br>
Building and maintaining large-scale ETL/ELT data pipelines<br>
<br>
Distributed computing (e.g., Spark / PySpark) for data processing and automation<br>
<br>
Query performance optimization and tuning at scale<br>
<br>
Hands-on experience with:<br>
<br>
Apache Spark and Airflow (or similar workflow/orchestration tools) for efficient large-scale data pipelines<br>
<br>
Data modeling, especially dimensional modeling, and designing schemas optimized for analytics and reporting<br>
<br>
Big data platforms and/or data lake architectures<br>
<br>
Experience with CI/CD tooling such as Jenkins (or similar tools)<br>
<br>
Experience with cloud technologies, AWS/GCP (e.g., S3, EMR, Lambda, Glue, RDS/Redshift, Big-query, Kinesis or similar services)<br>
<br>
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 .<br>
<br>
<b>Pay &amp; Benefits</b><br>
<br>
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.<br>
<br>
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.<br>
<br>
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.</p>

Sr. Data Engineer

<p>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 Books. 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.<br>
<br>
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.<br>
<br>
Come join us to build large-scale personalized recommender systems for Apps &amp; Games, Video, Fitness+, Podcast and Books Recommendations. See your work touch the lives of billions of Apple users worldwide.<br>
<br>
<b>Description</b><br>
<br>
In this role, you will be responsible for operationalizing machine learning models-from building real-time and batch inference pipelines to optimizing system performance, reliability, and experimentation velocity. You&rsquo;ll help bridge the gap between research and production by developing the infrastructure, tooling, and monitoring required to ship ML-driven features safely and efficiently.<br>
<br>
If you are an engineer who enjoys scaling ML solutions, building production-grade services, and driving experimentation across billions of users, this is your opportunity to make a meaningful impact.&quot;,&quot;responsibilities&quot;:&quot;Partner with ML researchers and product teams to transition models into production, ensuring reliability, scalability, and low latency.<br>
<br>
Design and implement robust inference services using object-oriented languages (e.g., Java, Scala, C++) that operate at scale across Apple platforms.<br>
<br>
Build and manage data pipelines and model execution frameworks to support both batch and streaming use cases.<br>
<br>
Develop tooling and infrastructure for model deployment, versioning, rollback, and online evaluation.<br>
<br>
Lead A/B testing efforts, including integration, metric tracking, experiment validation, and performance analysis.<br>
<br>
Collaborate with infrastructure teams to improve observability, alerting, and model health monitoring.<br>
<br>
Drive continuous improvement in latency, throughput, fault tolerance, and overall system reliability.<br>
<br>
<b>Preferred Qualifications</b><br>
<br>
Experience in batch and real-time inference serving, including autoscaling and traffic management.<br>
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Background in content recommendation systems, search ranking, or user engagement optimization.<br>
<br>
Experience with CI/CD workflows for ML systems, including safe model rollouts and shadow testing.<br>
<br>
Exposure to containerized deployments and orchestration (Kubernetes, Docker).<br>
<br>
Experience building and deploying production-grade applications using LLMs, including expertise in prompt engineering, RAG pipelines, and framework orchestration.<br>
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Proven track record of developing autonomous agents capable of multi-step reasoning, external tool integration, and complex task decomposition to solve open-ended problems.<br>
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Prior experience working on consumer-scale media products (apps, games, books, music, or video).<br>
<br>
<b>Minimum Qualifications</b><br>
<br>
MS or PhD in Computer Science, Software Engineering, or related field.<br>
<br>
8+ years of deep software engineering experience, with a strong background in building and deploying production machine learning systems. Experience in areas such as personalization, search, or recommendations is a plus.<br>
<br>
Experience with big data and stream processing frameworks like Spark, Flink, or Kafka.<br>
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Proficiency in object-oriented programming languages such as Java, Scala, or C++.<br>
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Experience building and maintaining large-scale distributed systems for ML workloads.<br>
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Deep understanding of ML model deployment pipelines, runtime optimization, and system integration.<br>
<br>
Familiarity with A/B testing frameworks, experimental design, and online evaluation.<br>
<br>
Strong focus on system reliability, latency, and observability in production environments.<br>
<br>
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 .<br>
<br>
<b>Pay &amp; Benefits</b><br>
<br>
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.<br>
<br>
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.<br>
<br>
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.</p>

Sr. Machine Learning Engineer - Recommendations & Personalization (Feature Engineering)

lululemon

who we are
<br><br>
lululemon is an innovative performance apparel company for yoga, running, training, and other athletic pursuits. Setting the bar in technical fabrics and functional design, we create transformational products and experiences that support people in moving, growing, connecting, and being well. We owe our success to our innovative product, emphasis on stores, commitment to our people, and the incredible connections we make in every community we're in. As a company, we focus on creating positive change to build a healthier, thriving future. In particular, that includes creating an equitable, inclusive and growth-focused environment for our people.
<br><br>
about this team
<br><br>
lululemon Engineering is dedicated to building secure, reliable, and performant products for our guests and partners. We embrace the philosophies of Agile, DevOps, and SRE to accelerate our development process and provide the most enjoyable, inclusive, and supportive work environment possible. We believe our journey is more fun when it is collaborative, as we focus on the future instead of the past. As an Engineer, you will work as part of a global team supported by our business and architecture partners to help us collaboratively develop and deliver industry leading technology solutions that drive lululemon’s business goals.
<br><br>
core responsibilities
<br><br>
As a Senior Engineer II, you will work as the technical leader for the product(s) your team delivers. You will be counted on as a leader in your technology space, as you contribute to all areas of development and operations (pre-production to production). As a Senior Engineer II, you will dedicate a fair amount of time to the planning and discovery of tools and practices inside your given area of expertise. You will apply that knowledge by working closely with Staff Engineers to promote platform level change. Senior Engineer IIs, take production readiness and performance personally and help drive continuous improvement. You will be part of a day-to-day production release team and may perform on-call support functions as needed. You will be considered the technical owner of the production system(s) you work on and focus on how your product(s) are delivered and how to optimize them for efficiency, security and reliability.
<br><ul>
<li>Main contributor for product roadmaps and reliability strategy</li>
<li>Partner with project management to deliver status and performance updates</li>
<li>Conduct research to aid in product development and tools selection</li>
<li>Provide an escalation point and participate in on-call support rotations</li>
<li>Actively monitor key metrics, reports on trends, and make improvement recommendations</li>
<li>Facilitate an Engineering Community of Practice for your product(s)</li>
<li>Contribute to engineering automation, management or development of production level systems</li>
<li>Review product roadmaps and guide intake acceptance for a set of production systems</li>
<li>Own reliability for a defined set of production systems</li>
<li>Own the delivery lifecycle for a defined set of production systems</li>
</ul>
qualifications
<br><ul>
<li>Completed Bachelor’s degree or diploma (or equivalent experience) in Computer Science, Software Engineering or Software Architecture preferred; candidates with substantial and relevant industry experience are also eligible</li>
<li>Eight+ years of engineering experience</li>
<li>Ability to learn, understand, and work quickly with new emerging technologies, methodologies, and solutions in the Cloud/IT technology space</li>
<li>Apply proven SRE methodologies to maintain system reliability, scalability, and rapid incident recovery.</li>
<li>Architect and oversee infrastructure platforms that enable efficient development, deployment, and operational excellence.</li>
<li>Implement robust alerting strategies to detect anomalies early and trigger rapid response actions.</li>
<li>Design comprehensive monitoring solutions that track performance metrics, system health, and user experience.</li>
<li>Leverage Datadog for real‑time observability, analytics, and integration across applications and services.</li>
<li>Utilize Splunk to collect, index, and analyze log data for security, compliance, and operational insights.</li>
<li>Incorporate Quantametrics to deliver deep performance benchmarking and optimization recommendations.</li>
<li>Ability to assume the leadership/mentorship of Engineers</li>
</ul>
must haves
<br><ul>
<li>Acknowledge the presence of choice in every moment and take personal responsibility for your life.</li>
<li>Possess an entrepreneurial spirit and continuously innovate to achieve great results.</li>
<li>Communicate with honesty and kindness and create the space for others to do the same.</li>
<li>Lead with courage, knowing the possibility of greatness is bigger than the fear of failure.</li>
<li>Foster connection by putting people first and building trusting relationships.</li>
<li>Integrate fun and joy as a way of being and working, aka doesn’t take yourself too seriously.</li>
</ul>
additional notes
<br>Authorization to work in the United States is required for this role.
<br><br>
compensation and benefits package
<br><br>
lululemon’s compensation offerings are grounded in a pay-for-performance philosophy that recognizes exceptional individual and team performance. The typical hiring range for this position is from $136,200 - $178,700 annually; the base pay offered is based on market location and may vary depending on job-related knowledge, skills, experience, and internal equity. As part of our total rewards offering, permanent employees in this position may be eligible for our competitive annual bonus program, subject to program eligibility requirements.
<br><br>
At lululemon, investing in our people is a top priority. We believe that when life works, work works. We strive to be the place where inclusive leaders come to develop and enable all to be well. Recognizing our teams for their performance and dedication, other components of our total rewards offerings include support of career development, wellbeing, and personal growth:
<br><ul>
<li>Extended health and dental benefits, and mental health plans</li>
<li>Paid time off</li>
<li>Savings and retirement plan matching</li>
<li>Generous employee discount</li>
<li>Fitness & yoga classes</li>
<li>Parenthood top-up</li>
<li>Extensive catalog of development course offerings</li>
<li>People networks, mentorship programs, and leadership series (to name a few)</li>
</ul>
<b>Note:</b> The incentive programs, benefits, and perks have certain eligibility requirements. The Company reserves the right to alter these incentive programs, benefits, and perks in whole or in part at any time without advance notice.
<br><br>
workplace arrangement
<br><br>
In-person collaboration and connection is important to our culture. Work is performed onsite, minimum 4 days per week.
<br><br>
#LI-Onsite
<br><br>
#LI-VJ1

Senior Engineer II - Digital Platforms - SRE/Datadog

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