332 jobs for "Staff Network Engineer"

Senior Staff Machine Learning Engineer, ML Platform

At Apple - Cupertino

Posted on Oct 19

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Staff ML Engineer - Ads ML Infrastructure

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Senior Staff Engineer, Software Defined Dataplane

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Posted on Nov 2

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At Leidos - Farnborough

Posted on Nov 4

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Systems Engineer

At Leidos - Arlington

Posted on Nov 4

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Senior Staff Engineer, Software Defined Dataplane

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Assistant Federal Security Director - Generalist

At Transportation Security Administration - Billings

Posted on Nov 7

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Test Engineer IV

At Jabil - Guadalajara

Posted on Nov 5

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Assistant Federal Security Director-Generalist

At Transportation Security Administration - Bentonville

Posted on Oct 27

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COORDENADOR DE ENGENHARIA

At Jabil - Manaus

Posted on Nov 5

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Ingeniero de Automatizacion I

At Jabil - Tijuana

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Apple

Senior Staff Machine Learning Engineer, ML Platform

Cupertino, CA$262,500 – $394,000Posted 20 days ago

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At Apple, we work every day to create products that enrich people's lives. Apple Ads makes it possible for people around the world to easily access informative and imaginative content on their devices while helping publishers and developers promote and monetize their work. Today, our technology and services power advertising in Search Ads, App Store, and Apple News. Our platforms are highly-performant, deployed at scale, and setting new standards for enabling effective advertising while protecting user privacy.

The Machine Learning Platform team's mission is to empower teams at Apple Ads to easily and rapidly develop, deploy and operate innovative ML applications at scale by providing a self-serve, unified platform with foundational infrastructure in model training, inference and agentic AI, as well as associated data and application services.

Are you a results-oriented and versatile engineer who can excel in an Agile environment? You will work closely with other ML engineers and scientists to design, develop, and build world-class platform capabilities that will enable Apple Ads teams to improve and scale our ML features, models, and applications.

Description

The ML Platform team is responsible for bringing numerous features to advertisers and consumers while simultaneously supporting scalable modeling and continuous experimentation by all Apple Ads teams. As a key contributor to this team, you will design and develop model training and fine-tuning infrastructure at scale. You will enjoy building high-performing, elegant machine learning systems from the ground up, in close partnerships with various teams, both within and outside Apple Ads. You will also possess keen judgment in selecting technologies and building the right solution for the interesting challenges we get to tackle here. You will have the opportunity to define and refine architectures to meet the unique ad network challenges we must solve. You will play a meaningful role building machine learning products which deliver on Apple's privacy commitments and change the way advertising works with data.

Join us and contribute to a culture that emphasizes reliability, simplicity, and scalability. You will join a team of world-class machine learning engineers hungry to apply leading-edge technologies to deliver extraordinary experiences to our customers. We are one team, nurturing each other's growth and supporting each other in delivering for our customers!

Preferred Qualifications

Prior experience in privacy-preserving ML using techniques such as federated learning and differential privacy

Experience with LLM training and inference - pre-training, SFT, verifiable RL rewards, inference-Familiarity with Agentic AI

PhD/MS/BS in Computer Science or related field with 10+ years of industry experience in building ML systems

Minimum Qualifications

Experience building shared ML platforms, frameworks or services used by multiple teams or organizations.

Deep understanding of the ML lifecycle, including training pipelines, evaluation methodologies, and deployment patterns.

Deep understanding of deep learning architectures (Transformers, LLMs, DNNs) and training frameworks (TensorFlow, PyTorch)

Prior experience applying ML at scale in Ads, recommender systems, information retrieval or related domains.

Prior experience in distributed training at scale and optimization techniques like model pruning, compression, quantization & distillation.

Prior experience building AI/ML tooling for model fine-tuning and training, and/or infrastructure at scale

Ability to communicate effectively, both written and verbal, with technical and non-technical multi-functional teams

Results oriented with strong technical leadership skills and a desire to work in a fast-paced collaborative work environment

Curious business attitude with a proven ability to seek projects with a sense of ownership.

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 $262,500 and $394,000, 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

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