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Mobile Machine Learning Jobs in Renton, WA (NOW HIRING)

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Mobile Machine Learning information

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How much do mobile machine learning jobs pay per hour?

As of Sep 10, 2026, the average hourly pay for mobile machine learning in Renton, WA is $28.49, according to ZipRecruiter salary data. Most workers in this role earn between $16.20 and $22.69 per hour, depending on experience, location, and employer.

What is mobile machine learning?

Mobile machine learning refers to the development and deployment of machine learning models on mobile devices such as smartphones and tablets. It enables apps to perform tasks like image recognition, language translation, and speech processing directly on the device without needing to send data to the cloud. This approach improves privacy, reduces latency, and can work even without an internet connection. Developers use frameworks like TensorFlow Lite, Core ML, and PyTorch Mobile to optimize models for the limited resources of mobile hardware.

What are some common challenges faced by mobile machine learning engineers when deploying models on mobile devices?

Mobile Machine Learning engineers often encounter challenges related to limited computational resources and memory constraints on mobile devices. Optimizing models for efficient inference without significant loss in accuracy is a key hurdle, as is ensuring compatibility across different devices and operating systems. Additionally, balancing power consumption and real-time performance is critical, so engineers frequently collaborate with mobile app developers and hardware specialists to deliver seamless user experiences while maintaining model integrity.

What are the key skills and qualifications needed to thrive as a mobile machine learning engineer, and why are they important?

To thrive as a Mobile Machine Learning Engineer, you need a solid background in computer science, machine learning, and mobile application development, often supported by a relevant degree and experience. Proficiency with ML frameworks (like TensorFlow Lite or Core ML), mobile platforms (Android/iOS), and deployment tools is typically required. Strong problem-solving skills, adaptability, and effective communication set standout professionals apart in this field. These skills are crucial for successfully developing, optimizing, and integrating machine learning models into efficient and user-friendly mobile applications.

What is the difference between Mobile Machine Learning vs Data Scientist?

AspectMobile Machine LearningData Scientist
Required CredentialsBachelor's in CS, ML, or related; experience with mobile platformsBachelor's or higher in CS, Statistics, or related; data analysis skills
Work EnvironmentMobile app development teams, on-device processingData analysis teams, research environments
Industry UsageMobile app companies, tech startupsFinance, healthcare, tech firms
Common Search/ComparisonYesYes

Mobile Machine Learning focuses on developing ML models optimized for mobile devices and integrating them into mobile apps. Data Scientists analyze large datasets to extract insights and build predictive models across various industries. While both roles require programming and ML knowledge, Mobile Machine Learning emphasizes on-device deployment and mobile platform expertise, whereas Data Scientists focus on data analysis and model development for broader applications.

What are the most commonly searched types of Machine Learning jobs in Renton, WA?

The most popular types of Machine Learning jobs in Renton, WA are:

What are popular job titles related to Mobile Machine Learning jobs in Renton, WA?

For Mobile Machine Learning jobs in Renton, WA, the most frequently searched job titles are:

What cities near Renton, WA are hiring for Mobile Machine Learning jobs?

Cities near Renton, WA with the most Mobile Machine Learning job openings:

Mobile Machine Learning jobs near you
Infographic showing various Mobile Machine Learning job openings in Renton, WA as of September 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $59,251 per year, or $28.5 per hour.

Staff Machine Learning Engineer, Diffusion, Generative Modeling and Inference

Seattle, WA • On-site

Snapchat
Marketing • 1 - 5K employees
Learn more about Snapchatexternal

Full-time

Medical

Posted 26 days ago

Job description

Snap Inc is a technology company. We believe the camera presents the greatest opportunity to improve the way people live and communicate. Snap contributes to human progress by empowering people to express themselves, live in the moment, learn about the world, and have fun together.


The Company operates Snapchat, a visual messaging app that enhances your relationships with friends, family, and the world, and Specs Inc., a wholly-owned subsidiary dedicated to making computing more human, in addition to Bitmoji, Saturn, and other digital services.


Snap's Generative ML Platform team builds cutting-edge AI technologies that power creative, scalable experiences for hundreds of millions of Snapchatters worldwide. From multimodal LLMs and video generation to real-time AR, human understanding, and 3D content creation, we develop the full stack of generative AI, including foundational models, efficient infrastructure, and on-device and server-side inference. Our team creates intuitive tools, platforms, and agentic systems that empower creators, developers, and internal teams to bring ideas to life, while advancing personalized, human-centric experiences across mobile, web, and wearable devices like Spectacles.

We're looking for a Machine Learning Engineer to join Snap Inc!

What you'll do:

  • Develop innovative machine learning technology and products that serve millions of Snapchatters

  • Build cutting-edge augmented reality experiences using generative models

  • Deliver generative machine learning experiences on device

  • Partner with cross-functional Snap teams to explore and prototype new products

Knowledge, Skills & Abilities:

  • A proven passion for machine learning; you stay up-to-date with research and are excited about prototyping new ideas quickly

  • Familiarity with Neural Networks and Deep Learning and Generative Modeling

  • Deep understanding of mathematics and/or machine learning algorithms

  • Desire to solve open ambiguous problems

  • Desire to grow professionally, learn and help others

  • Ability to effectively collaborate with internal teams and external partners

  • Ability to work independently

Minimum Qualifications:

  • Bachelor's degree in technical field such as computer science, mathematics, statistics or equivalent years of experience

  • 8+ years of post-Bachelor's machine learning or related experience; or a Master's degree in a technical field + 7+ years of post-grad ML or related experience; or a PhD in a related technical field + 4+ years of post-grad ML or related experience

  • Experience with Computer Vision or Generative Modeling techniques

  • Experience working with machine learning frameworks such as TensorFlow, PyTorch, JAX, MLX, scikit-learn, or related frameworks

Preferred Qualifications:

  • Advanced degree in computer science or related field

  • Experience training large-scale diffusion models for images, videos or 3D

  • Knowledge of distillation, quantization and model compression techniques

  • Knowledge of GPU, CPU, or NPU optimization techniques

  • Experience building and optimizing ML inference pipelines

  • Experience working with machine learning frameworks such as TensorFlow, PyTorch, JAX, MLX, scikit-learn, or related frameworks

If you have a disability or special need that requires accommodation, please don't be shy and provide us some information.

"Default Together" Policy at Snap: At Snap Inc. we believe that being together in person helps us build our culture faster, reinforce our values, and serve our community, customers and partners better through dynamic collaboration. To reflect this, we practice a "default together" approach and expect our team members to work in an office 4+ days per week.

At Snap, we believe that having a team of diverse backgrounds and voices working together will enable us to create innovative products that improve the way people live and communicate. Snap is proud to be an equal opportunity employer, and committed to providing employment opportunities regardless of race, religious creed, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex, gender, gender identity, gender expression, pregnancy, childbirth and breastfeeding, age, sexual orientation, military or veteran status, or any other protected classification, in accordance with applicable federal, state, and local laws. EOE, including disability/vets.

We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, where applicable).

Our Benefits: Snap Inc. is its own community, so we've got your back! We do our best to make sure you and your loved ones have everything you need to be happy and healthy, on your own terms. Our benefits are built around your needs and include paid parental leave, comprehensive medical coverage, emotional and mental health support programs, and compensation packages that let you share in Snap's long-term success!

Compensation

In the United States, work locations are assigned a pay zone which determines the salary range for the position. The successful candidate's starting pay will be determined based on job-related skills, experience, qualifications, work location, and market conditions. The starting pay may be negotiable within the salary range for the position. These pay zones may be modified in the future.

Zone A (CA, WA, NYC):

The base salary range for this position is $229,000-$343,000 annually.


Zone B:

The base salary range for this position is $218,000-$326,000 annually.

Zone C:

The base salary range for this position is $195,000-$292,000 annually.This position is eligible for equity in the form of RSUs.

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