17 jobs for "Senior ML Ecosystem Engineer"

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ML Model Integration Platform Eng

At Apple - Seattle

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Senior Machine Learning Engineer

At Apple

Posted on Oct 15

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Senior Machine Learning Engineer

At Apple

Posted on Oct 9

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Senior Data Scientist - Special Projects

At Apple - Cupertino

Posted on Oct 19

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Apple

Senior Cloud Engineer - Special Projects

Cupertino, CA$184,700 – $324,800Posted Oct 8, 2026

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Why you should apply for a job to Apple:

Ranked as one of the Best Technology Companies in 2020
3.7/5 in overall job satisfaction
3.1/5 in supportive management
66% say women are treated fairly and equally to men
65% would recommend this company to other women
66% say the CEO supports gender diversity

Ratings are based on anonymous reviews by Fairygodboss members. See all reviews ›

Apple's intelligent systems connect hardware, software, and services in ways that feel effortless and deeply personal. We're looking for an engineer who thrives at this intersection - someone who can design robust cloud infrastructure and services, build intelligent data pipelines, and turn complex, multi-modal data into clear and actionable insights.

You'll architect and operate the systems that power Apple's distributed AI experiences - from data pipelines processing large-scale device and server logs, to inference platforms hosting models for live and offline evaluation. Your work will help teams understand, optimize, and elevate the intelligence that drives Apple products.

Description

Our team works at the intersection of hardware, software, and intelligence. We design the systems, infrastructure, and tools that enable Apple's next generation of AI-driven experiences - from on-device middleware and distributed inference platforms to large-scale data pipelines, interactive analytics, and advanced developer tooling. We collaborate closely with hardware, robotics, ML, design, and platform teams to build end-to-end solutions that are performant, intuitive, and deeply integrated into Apple's ecosystem. The work is hands-on, highly cross-disciplinary, and central to shaping how Apple's intelligent systems evolve.","responsibilities":"Design, build, and maintain scalable cloud infrastructure and services supporting AI-driven products and experiments

Develop data pipelines that process and transform large volumes of multi-modal data

Implement inference platforms that host or proxy models for live inference, batch annotation, and large-scale evaluation

Design and build metrics dashboards, KPIs, and evaluation frameworks to measure data quality, model performance, and system health

Collaborate with data scientists, AI engineers, and platform teams to ensure reliable, traceable, and reproducible insights

Contribute to architecture and design reviews, and set best practices for data integrity, privacy, and secure compute

Work with evolving hardware to help bridge the gap between on-device data and cloud intelligence

Prototype novel approaches to data-driven performance analysis, scaling from experiment to production

Preferred Qualifications

Experience with multi-modal data systems

Background in robotics or simulation pipelines

Familiarity with distributed computation frameworks for workflow orchestration and large-scale data processing

Understanding of model lifecycle management and inference serving architectures

Knowledge of observability tooling and best practices for cloud infrastructure

Strong intuition for data quality metrics, evaluation design, and experiment analysis

Minimum Qualifications

Proven experience building distributed backend systems, web services, and data pipelines

Strong proficiency in one or more modern languages such as Python, Go, or Swift

Experience deploying, managing, and optimizing scalable cloud infrastructure on AWS, GCP, or other modern cloud platforms

Experience architecting and orchestrating resilient, distributed applications using Kubernetes or similar container orchestration frameworks

Deep understanding of cloud infrastructure, containerization, and CI/CD automation

Experience designing and operating ETL/ELT pipelines that transform diverse, large-scale data, including device telemetry, logs, or model outputs

Familiarity with data warehousing, SQL/NoSQL systems, and scalable storage architectures

Hands-on experience with data visualization, dash boarding, or metric evaluation frameworks

Strong focus on system reliability, observability, and performance tuning

Ability to collaborate effectively with hardware, user experience, AI, and robotics teams to shape system behavior end-to-end

Bachelor's or Master's degree in Computer Science, Data Engineering, or related field, and 5+ years of industry experience

Pay & 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 $184,700 and $324,800, 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.

About Apple

Working at Apple means doing more than you ever thought possible and having more impact than you ever imagined.

Size: 10,000+ employees
Industry: Technology: Manufacturing

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