data reporting analyst - production support engineer

full stack engineer - maps data platform workflow team

administrative assistant, hardware technology

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data engineer, part dataops

data reporting analyst - production support engineer Jobs in Cupertino

full stack engineer - maps data platform workflow team Jobs in Cupertino

full stack engineer maps data platform workflow team

Apple

The Maps Data Platform Workflows Team oversees the processing and management of data and workflows at the core of Apple Maps. We build and maintain the systems that enable processing and workflow management of petabytes of map data that powers the Apple Maps experience used by millions of people every day! 
 
As a Maps Data Platform engineer, youʼll design and help implement systems which empower teams across engineering and operations to build our future Apple Maps experiences! 
 
Description 
 
The Maps Data Platform Workflows Team builds and maintains the foundation that powers Apple Maps. We are responsible for providing scalable and extensible workflows that handles petabytes of map data, enabling various aspects of Map building including but not limited to data ingest, map updates, review process, and traceability. 
 
As a full-stack engineer on the team, you will primarily be responsible to build user experiences that powers various workflows involved in Map building life cycle. This position is ideal for innovative engineers who are passionate and excited to work in complex, fast-paced and ambiguous environments to deliver tangible results keeping in mind our end users and their experiences.&quot;,&quot;responsibilities&quot;:&quot;Build user experiences that powers various workflows involved in Map building life cycle. 
 
Implement foundational platform components to support Generative-AI based multi agent systems. 
 
Work closely with multi functional teams to enhance and improve our workflow solutions. 
 
Design and implement scalable and extensible platform components to support the user experiences across a dynamic range of use cases. 
 
Implement foundational platform components to to support Generative-AI based multi agent systems. 
 
Partner with a wide array of cross functional partner teams and stakeholders to understand the requirements to help build the best-in-class user experiences. 
 
Drive end-to-end delivery of the software projects and enable platform users across the Maps organization. 
 
Support and improve new and existing user experiences that power Apple Maps. 
 
Preferred Qualifications 
 
Experience with platform based approach to building user experiences with integration with REST and/or GraphQL APIs to enable scalability and reusability. 
 
Experience with Geospatial applications or mapping libraries (Mapbox, Leaflet or similar) 
 
Understanding of authentication and authorization mechanisms, including JWT and OAuth. 
 
Proven success applying Generative AI to production systems beyond prompt engineering. 
 
Minimum Qualifications 
 
Bachelor&rsquo;s degree and 4+ years of experience building and maintaining production systems. 
 
Strong hands-on experience with React, including hooks, context, and performance optimization techniques. Proficiency in TypeScript for building scalable and maintainable frontend applications. 
 
Experience with modern state management solutions such as Redux Toolkit, React Query, or Apollo. 
 
Familiarity with data visualization and charting libraries such as Highcharts, Recharts, Chart.js, or D3. 
 
Solid understanding of component-based architecture and reusable UI patterns. 
 
Experience in building scalable and low latency JVM-based web services using Scala or Java. 
 
Strong understanding of distributed data storage systems (both databases and indexes). 
 
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant . 
 
Pay &amp; Benefits 
 
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $147,400 and $272,100, and your base pay will depend on your skills, qualifications, experience, and location. 
 
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits. 
 
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

Full Stack Engineer - Maps Data Platform Workflow Team

The Intelligence Platform team empowers clients across Apple&rsquo;s operating systems with a high quality user-centric search and data platform, and the primary inference platform that enable next generation user experiences for Apple Intelligence. We are in search of an accomplished and driven Machine Learning Engineer who has a robust understanding of Large Language Models, Generative AI and high-performance systems computing. Your primary role will involve working with our cross-functional teams that build foundation models, as well as our client teams that want to run inference using these models and continue the development of our inference stack. By contributing to our team, you&rsquo;ll play an integral part in developing Siri, Photos, Music, and various other services, leaving a significant footprint on the evolution of our AI platforms. Join us in our exciting journey as we push the frontiers of Machine Learning and Generative AI. Your expertise and contributions will be invaluable in shaping the future of our Intelligence Platform. 
 
Description 
 
As a Machine Learning Engineer on the Apple Intelligence Platform Inference Tean, you&rsquo;ll join a phenomenal team of top-performing engineers and and will be entrusted with a range of responsibilities. Your tasks will include: 
 
Leading the exploration and application of Large Language Models and Generative AI, venturing into new areas within these fields. 
 
Translating the latest research into high-performing systems and a model serving stack that can be practically applied to enhance user experiences. 
 
Contribute to setting the team&rsquo;s strategic direction, cultivating an environment that encourages innovation and professional growth. 
 
Collaborating with various teams to develop and implement evolving requirements of our clients on the GenAI inference stack, ensuring performance optimization and alignment with broader business goals. 
 
Preferred Qualifications 
 
An advanced degree (Master&rsquo;s or Ph.D.) in Computer Science, Artificial Intelligence, Machine Learning, or a related field is required 
 
Ongoing professional development in Machine Learning and Artificial Intelligence domains is expected. 
 
Minimum Qualifications 
 
In-depth experience in Machine Learning, with a particular emphasis on Large Language Models (LLMs) and Generative AI. 
 
Published research in the field of Machine Learning or AI is highly desirable, indicating an ability to not only understand but also contribute to cutting-edge research. 
 
Proven ability to comprehend, interpret, and apply cutting-edge research into tangible applications. 
 
Proven problem-solving and leadership abilities, with the capacity to steer the team&rsquo;s research and practical applications in a collaborative and fast-paced environment. 
 
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant . 
 
Pay &amp; Benefits 
 
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $147,400 and $272,100, and your base pay will depend on your skills, qualifications, experience, and location. 
 
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits. 
 
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

Machine Learning Engineer - Large Language Models & Generative AI Inference

At Apple, we believe that innovation flourishes in an environment where ideas are challenged, collaboration is encouraged and technology is pushed to its limits. This environment is only possible when diverse minds come together, bringing unique perspectives and experiences. Our people and their ideas inspire innovation in everything we do. Imagine what you could accomplish here! Join Apple and help us make the world a better place. 
 
As a principal contributor in our Apple Data Platform SRE organization you will apply SRE principles as you mentor and partner with our engineers and partner teams, ensuring petabyte-scale analytics infrastructure runs reliably and efficiently. This role focuses on managing bare-metal and cloud based infrastructure, levering and extending our infrastructure-as-code based tooling, analyzing and optimizing performance, helping to plan and execute long term fleet management logistics, capacity planning, and ultimately maintaining operational excellence across distributed data platforms that power analytics across Apple. This role includes production on-call responsibilities. 
 
Description 
 
Apple Service Engineering (ASE) teams build and scale the platforms and infrastructure behind many of Apple's services (such as iCloud, iTunes, Siri, and Maps). We are the foundation on which Apple's software developers build the products that our customers love. We are looking for a passionate and dedicated Senior Site Reliability Engineer to provide technical leadership on our team to help ensure our customers have the highest quality Apple Services experience. The Apple Data Platform (ADP) Compute SRE team is responsible for the core infrastructure, including our legacy bare-metal platforms and modern cloud based infrastructure stack. We partner with both peer SRE teams and several of our world-class software and product engineering teams to support infrastructure reliability, multi-year parallel migrations for Apple properties, as well as the automation, tooling, incident, and process management necessary to ensure smooth 24x7 operations for ADP customers.&quot;,&quot;responsibilities&quot;:&quot;Principal/Lead SRE for ADP Compute SRE team, mentoring other ICs, and partnering with other senior engineers to ensure service architecture, tooling, design, and implementations are of the highest quality. 
 
Identifying efficiency improvements in technical operations and training partner teams, leading by example. 
 
Managing infrastructure fleet capacity, growth, and hardware lifecycle with innovative tooling, effective planning, and proactive check-ins with our leadership and program management teams. 
 
Providing technical leadership for Hadoop and Kubernetes infrastructure, tooling (including infrastructure-as-code), and services. 
 
Programming in Python and Golang supported by Generative AI tooling to accelerate development of mission critical automation and tools. 
 
Proactive collaboration and presentation skills to effectively communicate ideas and represent the deliverables and needs of the SRE team with ASE leadership. 
 
Production on-call and incident management responsibilities. 
 
Preferred Qualifications 
 
15+ YoE in SRE or related work managing infrastructure at scale 
 
Experience with scale testing, disaster recovery, and capacity planning 
 
Ability to define the technical roadmap for infrastructure and drive cross-functional alignment on architectural standards and best practices 
 
Minimum Qualifications 
 
BS/MS in Computer Science or Equivalent 
 
12+ years of experience in Site Reliability Engineering, managing infrastructure and services at scale 
 
5+ years of experience in management or technical leadership roles 
 
History of end-to-end project management and delivery 
 
Demonstrable programming skills to both develop software/tools and lead code reviews 
 
Experience managing Hadoop and Kubernetes infrastructure and related services, or equivalent experience 
 
Advanced knowledge of Linux, Networking, and Containers 
 
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant . 
 
Pay &amp; Benefits 
 
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $181,100 and $318,400, and your base pay will depend on your skills, qualifications, experience, and location. 
 
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits. 
 
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

Senior Site Reliability Engineer, Apple Data Platform Infra SRE

We are looking for a Senior Software Engineer to join our Data Engineering Infrastructure team, which builds and operates the foundational platforms that power data ingestion, transformation, and analytics across the organization. You will design and develop high-performance, reliable, and scalable systems that enable data engineers, analysts, and ML practitioners to move, process, and govern data efficiently and securely. 
 
Description 
 
As a Senior Software Engineer in the Data Engineering Infrastructure team, you will design and build distributed systems and frameworks that automate the lifecycle of data - from ingestion to transformation to serving. You&rsquo;ll work at the intersection of software engineering, distributed data processing, and cloud infrastructure, helping to define the standards, abstractions, and tools that enable our data platform to operate at scale. 
 
You will collaborate closely with teams across data engineering, analytics, ML, and platform engineering to deliver resilient infrastructure components such as data ingestion pipelines, metadata and schema management services, workflow orchestration, and monitoring frameworks. This is a hands-on role where you will influence architecture, write production-grade code, and drive engineering excellence across the data platform.&quot;,&quot;responsibilities&quot;:&quot;Design, build, and maintain scalable data infrastructure and frameworks supporting batch and streaming workloads. 
 
Develop common services for data ingestion, schema evolution, metadata management, and data quality enforcement. 
 
Implement automation for data pipeline deployment, monitoring, and governance. 
 
Collaborate with data engineers and platform teams to define APIs, SDKs, and libraries that make developing data applications simpler and safer. 
 
Improve performance, reliability, and observability of data pipelines and platform components. 
 
Participate in architecture reviews, code reviews, and technical design discussions. 
 
Drive adoption of best practices in distributed systems, storage formats (Parquet, Iceberg), and data access layers. 
 
Contribute to capacity planning, cost optimization, and operational excellence in cloud and on-prem environments. 
 
Mentor junior engineers and contribute to the overall technical strategy and roadmap for the data platform. 
 
Preferred Qualifications 
 
Deep expertise in optimizing and troubleshooting distributed data frameworks (e.g., Apache Spark internals, Flink stateful streaming, Kafka Connect) 
 
Advanced experience with workflow orchestration tools (e.g., Airflow, Prefect, Dagster), including custom development 
 
Proven track record in performance tuning, cost optimization, and designing comprehensive observability solutions for large-scale cloud data platforms 
 
Familiarity with data security, privacy, and compliance principles within data infrastructure 
 
Experience integrating data platforms with MLOps and machine learning workflows 
 
Active participation or contributions to relevant open-source data technologies or industry communities 
 
Master&rsquo;s or Ph.D. degree in Computer Science, Data Engineering, or a related quantitative field 
 
Minimum Qualifications 
 
12+ years of experience in software engineering, with at least 5 years focused on data systems or platform infrastructure 
 
Proven track record of leading design discussions, mentoring engineers, and driving cross-team technical initiatives 
 
Strong programming skills in Java, Python; Scala - nice to have 
 
Hands-on experience designing, developing, and operating high-performance backend services 
 
Hands-on experience with distributed data frameworks such as Spark, Flink, or Kafka 
 
Solid understanding of data modeling, storage formats (Parquet/Avro/ORC), and partitioning strategies 
 
Experience with data governance, cataloging, and schema management systems (e.g., Hive Metastore, Glue, Iceberg, Delta Lake) 
 
Experience working with cloud-based data platforms (AWS, GCP, or Azure) 
 
Experience building data infrastructure frameworks, SDKs, or shared libraries used by multiple data teams 
 
Familiarity with CI/CD, container orchestration (Kubernetes), and infrastructure-as-code tools (Terraform, CloudFormation) 
 
Excellent problem-solving, debugging, and communication skills 
 
Bachelor&rsquo;s degree in Computer Science, Engineering, or related field (or equivalent practical experience) 
 
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant . 
 
Pay &amp; Benefits 
 
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $181,100 and $318,400, and your base pay will depend on your skills, qualifications, experience, and location. 
 
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits. 
 
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

Senior Software Engineer - Data

Amazon Web Services

<div><h2 class="jobSectionHeader">DESCRIPTION</h2><div>
AWS's Trainium and Inferentia chips power the world's largest machine learning clusters. Our team builds virtual platforms &mdash; full-system C++ and SystemC models of these custom SoCs &mdash; that let software teams start development months before silicon arrives. For Trainium3, our virtual platform enabled running a full training workload within 12 hours of first silicon. We're looking for a software engineer to build and own the models and infrastructure that make this possible. 
 
What you'll do: 
<ul><li>Build and own functional models of SoC subsystems that integrate into our full-system virtual platform, used by firmware, driver, runtime, and application software teams</li><li>Design models for usability and performance &mdash; your customers are software engineers who need to run real workloads on your platform efficiently</li><li>Develop and improve the virtual platform infrastructure: QEMU integration, simulation performance, build and release tooling, and customer-facing documentation</li><li>Work with software teams (your primary customers) to understand their workflows, debug issues on the platform, and shape the model to maximize their productivity</li><li>Drive simulation performance improvements so the platform can handle increasingly complex workloads at scale</li><li>Contribute to model architecture decisions &mdash; choosing the right level of abstraction and fidelity for each subsystem based on customer needs</li></ul> 
Why this role is interesting: 
<ul><li>You'll own a product that software teams across AWS depend on &mdash; they literally can't start development without your virtual platform</li><li>The engineering challenges are genuinely interesting: full-system simulation, multi-subsystem integration, QEMU development, performance optimization at scale</li><li>You'll see the direct impact of your work when software teams hit the ground running on new silicon</li><li>As the team grows, there's a path into architectural modeling &mdash; using the platform to explore design alternatives and influence chip architecture</li><li>Small team, startup pace, big impact inside AWS's custom silicon org</li></ul> 
You will thrive in this role if you: 
 
<ul><li>Have built functional models, virtual platforms, or system-level simulations for SoCs, ASICs, GPUs, or CPUs</li><li>Think of yourself as a software engineer first, with deep domain knowledge in chip architecture</li><li>Are comfortable in C++ or SystemC, and familiar with Python for tooling</li><li>Care about your customers' experience &mdash; you think about usability, documentation, and reliability, not just model accuracy</li><li>Are interested in expanding into performance or architectural modeling as the team scales</li><li>Enjoy working on a small, high-impact team where you own significant pieces of the stack</li></ul> 
No ML background needed. You'll learn the ML accelerator domain on the job. 
 
This role can be based in Cupertino, CA or Austin, TX.</div><h2 class="jobSectionHeader">
BASIC QUALIFICATIONS</h2><ul><li>Experience programming languages such as C/C++, Python, Java or Perl</li><li>2+ years writing functional models, virtual platforms, or system-level simulations for hardware (SoCs, ASICs, GPUs, CPUs)</li><li>Familiarity with SoC, CPU, GPU, and/or ASIC architecture and micro-architecture</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>2+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience</li><li>Experience developing for or integrating with QEMU</li><li>Experience with SystemC, TLM, or transaction-level modeling</li><li>Experience building simulation infrastructure, CI pipelines, or release tooling</li><li>Familiarity with Modern C++ (20 and beyond)</li><li>Experience with PyTest, GoogleTest, or similar test frameworks</li><li>Experience with multi-threaded programming</li><li>Familiarity with firmware, driver, or runtime software development</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, Cupertino - 165,200.00 - 223,600.00 USD annually 
USA, TX, Austin - 143,700.00 - 194,400.00 USD annually</div>

Virtual Platform Software Engineer, Annapurna Labs Machine Learning Accelerators, AWS

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. 
 
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. 
 
Description 
 
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. 
 
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. 
 
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. 
 
Develop APIs, libraries, and services that improve the efficiency and usability of large-scale ML training and inference pipelines. 
 
Optimize performance and resource utilization across GPU/CPU clusters for ML workloads running at Apple scale. 
 
Collaborate with ML teams to understand model and pipeline needs and translate them into robust platform features. 
 
Design fault-tolerant orchestration mechanisms, autoscaling strategies, and runtime improvements for distributed ML jobs. 
 
Diagnose complex issues across distributed systems and ML pipelines to ensure reliability and availability. 
 
Improve observability, monitoring, and debugging capabilities targeted at ML-centric distributed workloads. 
 
Contribute to architectural decisions and, where appropriate, upstream enhancements to Ray and related tools. 
 
Preferred Qualifications 
 
Experience with distributed training frameworks (DeepSpeed, Horovod, FSDP, ZeRO). 
 
Background in optimizing GPU workloads or performance benchmarking. 
 
Experience with model orchestration systems or ML platforms. 
 
Contributions to open-source ML or distributed systems projects. 
 
Familiarity with large-scale data systems such as Spark, Flink, or similar. 
 
Minimum Qualifications 
 
6+ years building distributed systems, high-scale backend services, or compute runtimes. 
 
Solid background in ML workflows, model training, model serving, or data pipeline development. 
 
Proficiency in Python, plus strong experience in a systems-level language (C++, Rust, Go, or Java). 
 
Experience with ML frameworks such as PyTorch or TensorFlow and familiarity with GPU-based training. 
 
Understanding of parallelism strategies, model scaling, or distributed training concepts. 
 
Experience with cluster orchestration (Kubernetes, EKS, GKE) or large-scale compute systems. 
 
Strong debugging skills across distributed and ML-centric runtime environments. 
 
Ability to work cross-functionally with ML engineers, data engineers, and infrastructure teams. 
 
B.S., M.S., or Ph.D. in Computer Science, Machine Learning, or related technical fields - or comparable software engineering experience. 
 
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant . 
 
Pay &amp; Benefits 
 
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $147,400 and $272,100, and your base pay will depend on your skills, qualifications, experience, and location. 
 
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits. 
 
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

Senior ML Engineer, Apple Ray, Apple Data Platform

Catalyst Labs

<div>
 
 About The Job ML Engineer
 
 
 
 
 Our Client
 
 
 
 Is a rapidly growing Tier 1 VC backed startup based in New York with $60 million in funding revolutionizing how outside sales and service teams work. Their AI technology captures and analyzes real-world conversations, providing full visibility into every customer interaction without the need for traditional ride-alongs.
 
 
 By turning field conversations into searchable, actionable data, they empower teams to coach more effectively, close more deals, and boost average ticket sizes. Combining cutting-edge AI with a deep understanding of field sales dynamics, this company is redefining how businesses learn from and optimize their in-person customer experiences.
 
 
 
 About Us
 
 
 
 Catalyst Labs is a leading talent agency with a specialized vertical in Applied AI, Machine Learning, and Data Science. We stand out as an agency that&rsquo;s deeply embedded in our clients&rsquo; recruitment operations.
 
 
 We collaborate directly with Founders, CTOs, and Heads of AI in those themes who are driving the next wave of applied intelligence from model optimization to productized AI workflows. We take pride in facilitating conversations that align with your technical expertise, creative problem-solving mindset, and long-term growth trajectory in the evolving world of intelligent systems.
 
 
 
 Location
 
 : New York, NY
 
 
 
 Work type
 
 : Full Time,
 
 
 
 Compensation
 
 : above market base + bonus + equity
 
 
 
 Roles &amp; Responsibilities
 
 
 
 <ul>
 <li>
 Design, build, and deploy production-grade ML systems with end-to-end ownership of the model lifecyclefrom conception to deployment and maintenance.
 </li>
 <li>
 Architect and deliver AI-powered solutions enabling natural speech interaction and real-time audio understanding.
 </li>
 <li>
 Develop and optimize ML models focused on audio data to extract business-critical insights from previously unstructured voice data.
 </li>
 <li>
 Build agents capable of operating natively on real-world audio inputs.
 </li>
 <li>
 Collaborate with cross-functional teams to shape the foundations of the AI stack, improve tooling, and drive innovation in LLM and audio ML applications.
 </li>
 <li>
 Work directly with customers to identify needs, gather feedback, and deliver impactful real-world solutions.
 </li>
 <li>
 Handle the entire AI lifecycle, including data acquisition, preprocessing, model training, deployment, inference, and monitoring in production environments.
 </li>
 <li>
 Participate in continuous improvement of the ML infrastructure and processes for scalability and performance.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field.
 </li>
 <li>
 1-6 years of professional experience in ML engineering.
 </li>
 <li>
 Strong programming skills in Python (TypeScript experience is a plus).
 </li>
 <li>
 Hands-on experience with ML frameworks such as PyTorch or TensorFlow.
 </li>
 <li>
 Familiarity with cloud environments and infrastructure (preferably AWS).
 </li>
 <li>
 Strong understanding of data pipeline design, real-time inference, and model monitoring.
 </li>
 <li>
 Excellent communication skills with the ability to engage directly with customers and stakeholders.
 
 
 </li>
 </ul>
 
 Core Experience
 
 
 
 <ul>
 <li>
 Proven experience building and deploying ML models into production environments.
 </li>
 <li>
 Demonstrated ability to own the full model lifecyclefrom data ingestion and model development to deployment and monitoring.
 </li>
 <li>
 Experience with audio-focused ML projects or similar domains involving unstructured data.
 </li>
 <li>
 Proficiency in building scalable data pipelines for model training and evaluation.
 </li>
 <li>
 Familiarity with FastAPI, OpenAI APIs, Baseten, LiteLLM, LiveKit, PostgreSQL, Redis, and S3 is a plus.
 </li>
 <li>
 Solid grasp of ML systems architecture, feature engineering, evaluation strategies, and deployment best practices.
 </li>
 </ul>
</div>

ML Engineer

Explore 112+ Full stack engineer maps data platform workflow team in Cupertino this April. Find roles across top companies and apply now to boost your career.