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Summer Machine Learning Hardware Jobs in Seattle, WA

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Summer Machine Learning Hardware information

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$13

$27

$54

How much do summer machine learning hardware jobs pay per hour?

As of Aug 17, 2026, the average hourly pay for summer machine learning hardware in Seattle, WA is $27.99, according to ZipRecruiter salary data. Most workers in this role earn between $19.95 and $31.73 per hour, depending on experience, location, and employer.

What is the difference between Summer Machine Learning Hardware vs Summer Data Scientist?

AspectSummer Machine Learning HardwareSummer Data Scientist
Required CredentialsBachelor's or Master's in Computer Science, Electrical Engineering, or related fields; knowledge of hardware design and programmingBachelor's or Master's in Data Science, Statistics, or related fields; proficiency in data analysis and programming
Work EnvironmentHardware labs, R&D centers, tech companies focusing on AI hardwareOffice settings, research labs, tech companies analyzing data and building models
Industry UsageAI hardware development, embedded systems, hardware acceleration for MLData analysis, predictive modeling, AI application development

Summer Machine Learning Hardware roles focus on designing and optimizing hardware for machine learning applications, requiring technical skills in hardware engineering. In contrast, Summer Data Scientist positions involve analyzing data, building models, and deriving insights. Both roles are essential in AI development but differ in their technical focus and work environment.

Summer Machine Learning Hardware jobs near you

Software Engineer, Core Machine Learning

Meta

Bellevue, WA • On-site, Remote

$183K/yr

Full-time

Posted 24 days ago

Meta rating

7.8

Company rating: 7.8 out of 10

Based on 45 frontline employees who took The Breakroom Quiz

136th of 244 rated software companies

Job description

Meta is seeking a Staff Software Engineer to join the Core Machine Learning team, focused on building and scaling the foundational ML infrastructure and systems that power Meta's family of products. In this role, you will architect and deliver high-impact ML platform capabilities — spanning training infrastructure, model serving, feature engineering pipelines, and AI-accelerated developer tooling — that enable thousands of engineers and researchers across Meta to build and ship state-of-the-art machine learning models at scale.
Software Engineer, Core Machine Learning Responsibilities:
  • Architect and own large-scale ML infrastructure systems, including distributed training frameworks, model serving platforms, and feature computation pipelines that support production workloads across Meta's product surface
  • Lead the technical design and implementation of foundational ML platform components, evaluating trade-offs across performance, reliability, and developer experience
  • Drive end-to-end delivery of major ML infrastructure initiatives, coordinating across teams and disciplines to align on priorities, manage dependencies, and execute phased rollouts
  • Identify and resolve performance bottlenecks in ML training and inference systems through instrumentation, profiling, and targeted optimization
  • Define and enforce service level objectives for core ML platform services, building dashboards, alerting systems, and runbooks to reduce mean time to mitigation during incidents
  • Establish and advocate for engineering best practices in ML systems development, including testing strategies, safe rollout patterns, and AI-accelerated development workflows
  • Collaborate with research, product engineering, and infrastructure teams as a credible technical co-owner, independently driving design reviews, data analyses, and architectural decisions
  • Mentor other engineers on ML systems design, debugging complex distributed system issues, and applying AI tools to accelerate development velocity
  • Contribute to the team's technical roadmap by identifying opportunities to improve ML platform capabilities and obtaining buy-in from key stakeholders across the organization

Minimum Qualifications:
  • Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
  • 8+ years of experience in software engineering with a focus on machine learning systems, ML infrastructure, or large-scale distributed systems
  • Experience designing and implementing production ML systems such as distributed training frameworks, model serving infrastructure, or large-scale feature engineering pipelines
  • Experience leading major technical initiatives from design through production, including cross-team coordination and phased rollout management
  • Experience with performance analysis and optimization of ML training or inference workloads, including profiling, instrumentation, and bottleneck resolution
  • Experience communicating technical decisions and trade-offs in writing to both engineering and non-engineering stakeholders through design documents, architectural proposals, or postmortems

Preferred Qualifications:
  • Experience defining and operating ML platform reliability programs, including resiliency testing, SLO frameworks, and incident retrospective processes
  • Experience building or contributing to open-source ML frameworks or platform tooling such as PyTorch, TensorFlow, Ray, or similar systems
  • Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
  • Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
  • Experience applying AI-assisted development tools to accelerate engineering workflows, including code generation, automated testing, or intelligent debugging
  • Experience with hardware-software co-design for ML workloads, including quantization, model compression, or resource-efficient AI techniques
  • Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)

About Meta:
Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics.
Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.
Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at accommodations-ext@meta.com.
$183,997/year to $257,000/year + bonus + equity + benefits
Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta.

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