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Pattern Making Internship Jobs in Seattle, WA (NOW HIRING)

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Pattern Making Internship information

See Seattle, WA salary details

$12

$21

$33

How much do pattern making internship jobs pay per hour?

As of Aug 21, 2026, the average hourly pay for pattern making internship in Seattle, WA is $21.98, according to ZipRecruiter salary data. Most workers in this role earn between $18.32 and $23.80 per hour, depending on experience, location, and employer.

What is a pattern making internship?

A Pattern Making Internship is a training opportunity where aspiring fashion professionals learn how to create patterns for garments under the guidance of experienced pattern makers. Interns gain hands-on experience with drafting, cutting, and modifying patterns, which are the templates used to assemble clothing. This internship often involves working with both manual and digital tools, and offers exposure to the fashion design and production process. It's an essential step for those interested in a career in fashion design, garment construction, or technical design.

What are the typical responsibilities and learning opportunities for a pattern making intern?

As a Pattern Making Intern, you’ll assist senior pattern makers in drafting, modifying, and digitizing garment patterns, often using both manual and computer-aided design tools. You’ll likely attend fittings, help adjust patterns based on feedback, and work closely with designers and sample makers to ensure high-quality prototypes. This internship offers hands-on exposure to the full product development process, from initial sketches to finished samples, and is a great way to build technical skills while learning industry standards and workflows. Collaboration and communication with various departments, such as design and production, are common and provide valuable networking opportunities.

What are the key skills and qualifications needed to thrive as a pattern making intern, and why are they important?

To thrive as a Pattern Making Intern, you need a solid understanding of garment construction, basic sewing techniques, and familiarity with pattern drafting principles, often backed by coursework or a degree in fashion design. Proficiency with pattern making software like Gerber AccuMark or CLO 3D, along with experience using manual drafting tools, is highly valuable. Attention to detail, creativity, and effective communication are important soft skills for collaborating with design teams and interpreting creative briefs. These abilities ensure accurate pattern development, efficient workflow, and successful translation of designs into production-ready pieces.

What is the difference between Pattern Making Internship vs Pattern Designer?

AspectPattern Making InternshipPattern Designer
Required CredentialsBasic sewing skills, coursework in fashion design or pattern makingAdvanced knowledge of pattern drafting, fashion design degree or equivalent experience
Work EnvironmentInternship setting, supervised, entry-level tasksProfessional studio or fashion house, independent work, creative responsibilities
Industry UsageTraining role, learning phase in fashion industryFull-time role, responsible for creating patterns for collections

While a Pattern Making Internship provides hands-on training and foundational skills in pattern drafting, a Pattern Designer is a professional responsible for creating detailed patterns for garments. Internships are ideal for beginners, whereas Pattern Designers typically have more experience and advanced skills.

Pattern Making Internship jobs near you
Infographic showing various Pattern Making Internship job openings in Seattle, WA as of August 2026, with employment types broken down into 33% Internship, 34% Full Time, and 33% Part Time. Highlights an 100% In-person job distribution, with an average salary of $45,719 per year, or $22 per hour.

Software Development Engineer II, AWS SageMaker AI

Socket.dev

Bellevue, WA • On-site

$144 - $194/hr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 3 days ago

New

Job description

At AWS SageMaker AI, we're making it easy to build state-of-the-art foundation models on the cloud. Model Factory is our platform for building, training, customizing, and evaluating foundation models at scale. Instead of hand-chaining data prep, distributed training, evaluation, and deployment across thousands of GPU and AWS Trainium devices, Model Factory lets teams express the whole lifecycle as a single, contract-validated workflow - orchestrated, reproducible, and fully managed. As LLMs and Generative AI scale, Model Factory is the platform that turns frontier training research into a reliable, repeatable pipeline for our internal teams and customers.

We're looking for a Software Development Engineer to help design, build, and operate the distributed systems at the core of this platform - the orchestration engine, compute integrations, SDK and contract layer, and the infrastructure that runs large-scale training and customization jobs. You'll own components end-to-end, from design through delivery and on-call operations, and work closely with the ML scientists and platform teams who depend on Model Factory every day. You'll turn requirements into robust, scalable, supportable services that fit cleanly into the overall architecture, uphold a high engineering bar, and grow your scope and technical leadership as you go.

A successful candidate has a strong software-engineering foundation, writes high-quality distributed-systems and services code, communicates clearly, and is motivated to deliver results in a fast-paced, ambiguous environment.

Key job responsibilities
  • Design, build, test, and operate services that orchestrate foundation-model data preparation, training, evaluation, and deployment as reliable, contract-validated workflows.
  • Own delivery of individual components end-to-end - from design and implementation through deployment, monitoring, and on-call operations.
  • Build and extend compute-backend integrations and job launchers - submitting, monitoring, and recovering large-scale training jobs across SageMaker (Training/Processing/HyperPod), EMR, AWS Batch, and Kubernetes/EKS.
  • Improve the platform's resiliency and operability for long-running distributed jobs - checkpoint/resume, fault detection and recovery, retries, and observability (metrics, logging, experiment tracking).
  • Contribute to the SDK, workflow orchestration, and schema/contract layer that teams use to declare and run jobs, and to the CDK infrastructure that deploys the platform.
  • Integrate containerized training and evaluation frameworks (e.g., PyTorch/FSDP, verl, NeMo/Megatron) into the platform's task and recipe model.
  • Contribute to design and architecture discussions, write clear technical designs, and uphold engineering best practices (code review, testing, operational readiness).
  • Collaborate with ML scientists and internal customers to translate training requirements into reliable, self-service platform capabilities, and help onboard and mentor interns and new engineers as you grow.
Basic Qualifications
  • 3+ years of non-internship professional software development experience
  • 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
  • 1+ years of software development engineer or related occupational experience
  • 1+ years of designing and developing large-scale, multi-tiered, multi-threaded, embedded or distributed software applications, tools, systems, and services using: C#, C++, Java, or Perl experience
  • 1+ years of Object Oriented Design experience
  • Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, or a related field
  • Experience programming with at least one software programming language
Preferred Qualifications
  • 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
  • Bachelor's degree in computer science or equivalent
  • - Experience with workflow/pipeline orchestration (Airflow, Step Functions, or similar) and event-driven or service-oriented architectures.
  • - Experience with container and cluster compute (Kubernetes/EKS, Ray, Slurm, AWS Batch) and cloud infrastructure-as-code (AWS CDK/CloudFormation).
  • - Experience building and operating fully-managed cloud services at scale, including resiliency, checkpointing, and fault tolerance for long-running jobs.
  • - Familiarity with machine-learning / deep-learning training workflows, GPU/accelerator compute (SageMaker HyperPod, AWS Trainium, P5-class GPUs), or distributed-training frameworks (PyTorch FSDP, Megatron-LM, DeepSpeed, verl).

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’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 & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.

USA, WA, Bellevue - 143,700.00 - 194,400.00 USD annually

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