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Ml Inference Jobs in Seattle, WA (NOW HIRING)

Scale AI

ML Research Engineer, ML Systems

Seattle, WA · On-site

Responsibilities : • Build, profile and optimize our training and inference framework • Collaborate with ML teams to accelerate their research and development and enable them to develop the next ...

Designworks Talent

Inference Engineer

Bellevue, WA · Remote

$117K - $140K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

Inference Engineer Location: Hybrid | Bellevue, WA Area Titles: Senior and Staff (multiple roles ... Experience working at a hyperscaler, AI lab, GPU cloud provider, or large-scale ML infrastructure ...

Catalyst Labs

ML Engineer

Seattle, WA · On-site

... inference, and monitoring in production environments. • Participate in continuous improvement of the ML infrastructure and processes for scalability and performance. Qualifications : Required : • ...

Prime Team Partners

ML Research Scientist

Seattle, WA · On-site

$190/hr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Prototype and implement novel ML techniques for largescale inference * Design experiments, analyze ... results, and translate findings into productionready solutions * Collaborate with ML, systems, and ...

Prime Team Partners

ML Research Scientist

Seattle, WA · On-site

$190/hr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Prototype and implement novel ML techniques for largescale inference * Design experiments, analyze ... results, and translate findings into productionready solutions * Collaborate with ML, systems, and ...

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Showing results 21-40

All JobsMl Inference JobsMl Inference Jobs in Seattle, WA

Ml Inference information

See Seattle, WA salary details

$42.7K

$139.7K

$223.6K

How much do ml inference jobs pay per year?

As of Aug 19, 2026, the average yearly pay for ml inference in Seattle, WA is $139,680.00, according to ZipRecruiter salary data. Most workers in this role earn between $112,100.00 and $154,800.00 per year, depending on experience, location, and employer.

What is ML inference?

ML inference refers to the process of using a trained machine learning model to make predictions or decisions based on new data. After a model has been trained on historical data, inference is the phase where that model is deployed and used in real-world applications, such as recognizing speech, detecting objects in images, or recommending products. The focus in ML inference is on speed, efficiency, and scalability to ensure quick predictions, often in real time. This process is critical for practical applications like mobile apps, web services, and embedded systems. Optimizing inference involves reducing latency, memory usage, and computational requirements.

What are the key skills and qualifications needed to thrive in ML inference?

To thrive in ML Inference, you need a solid background in machine learning principles, programming (Python or C++), and experience with deploying models at scale, often supported by a degree in computer science or a related field. Familiarity with frameworks and tools such as TensorFlow, PyTorch, ONNX, and cloud platforms like AWS SageMaker or Google AI Platform is typically required. Strong problem-solving skills, attention to detail, and effective communication are crucial soft skills for collaborating with multidisciplinary teams and optimizing model performance. These skills ensure efficient, scalable, and reliable deployment of machine learning solutions in real-world applications.

What are some common challenges faced by ML inference engineers when deploying models to production?

ML Inference Engineers often encounter challenges such as optimizing model latency and throughput to meet production requirements, ensuring compatibility with diverse hardware environments, and managing model versioning and updates without disrupting service. Additionally, balancing resource utilization and inference accuracy while monitoring real-time performance metrics is crucial. Collaboration with data scientists, DevOps, and software engineers is typically essential to streamline deployment and maintain robust, scalable inference pipelines.

What is the difference between Ml Inference vs Data Scientist?

AspectML InferenceData Scientist
Required CredentialsKnowledge of machine learning models, programming skillsDegree in data science, statistics, or related fields
Work EnvironmentDeploying models in production, real-time data processingData analysis, model development, research
Industry UsageAI product deployment, software companiesResearch institutions, tech firms, consulting

ML Inference focuses on deploying trained models to make predictions on new data, often in real-time. Data Scientists develop and analyze models, working primarily in research and development. While both roles require understanding of machine learning, ML Inference emphasizes deployment and operationalization, whereas Data Scientists focus on model creation and analysis.

What are popular job titles related to Ml Inference jobs in Seattle, WA?

For Ml Inference jobs in Seattle, WA, the most frequently searched job titles are:

What job categories do people searching Ml Inference jobs in Seattle, WA look for?

The top searched job categories for Ml Inference jobs in Seattle, WA are:

What cities near Seattle, WA are hiring for Ml Inference jobs?

Cities near Seattle, WA with the most Ml Inference job openings:

Ml Inference jobs near you
Infographic showing various Ml Inference job openings in Seattle, WA as of August 2026, with employment types broken down into 1% Internship, 91% Full Time, 4% Part Time, and 4% Contract. Highlights an 81% Physical, 5% Hybrid, and 14% Remote job distribution, with an average salary of $139,680 per year, or $67.2 per hour.

Principal Software Engineer, Machine Learning Infrastructure

Snapchat

Bellevue, WA • On-site

$152K - $204K/yr

Full-time

Medical

Re-posted 11 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 Engineering teams build fun and technically sophisticated products that reach hundreds of millions of Snapchatters around the world, every day. We're deeply committed to the well-being of everyone in our global community, which is why our values are at the root of everything we do. We move fast, with precision, and always execute with privacy at the forefront.

We're looking for a Principal Software Engineer to join Snap's ML Inference team!

What you'll do:

  • Oversee technical strategy and architecture in ML Inference Platform services

  • Design, implement, and scale critical engineering components and services to support ML inference and deployment

  • Work across teams to understand product requirements, evaluate trade-offs, and deliver the solutions needed to build innovative products or services

  • Advocate for and apply best practices when it comes to availability, scalability, operational excellence, and cost management

  • Provide technical direction that influences the entire company

Knowledge, Skills & Abilities

  • Excellent programming and software design skills, including debugging, performance analysis, and test design

  • Proven track record of operating highly-available systems at scale

  • Ability to proactively learn new concepts and technology and apply them at work

  • Skilled at solving ambiguous problems

  • Strong collaboration and mentorship skills

Minimum Qualifications:

  • Bachelors in technical field such as computer science, mathematics, statistics or equivalent years of experience

  • 10+ years of post-Bachelor's software development experience; or a Master's degree in a technical field + 9+ year of post-grad software development experience; or a PhD in a related technical field + 6+ years of post-grad software development experience

  • 2+ years of experience with technical leadership or acting as the domain-expert to a technical organization

  • Experience in technical leadership/ownership and setting technical direction for engineering projects

  • Experience architecting, designing, and developing large scale distributed systems and high-throughput RPC services

Preferred Qualifications:

  • Advanced degree in a technical field such as computer science

  • Experience with cross platform development

  • Ability to promote product excellence and collaboration, driving a portfolio of concurrent engineering projects, from short-term critical feature launches to long-term research initiatives.

  • Ability to create a compelling vision for the future, communicate clearly, and have a collaborative leadership approach.

  • Experience with Tensorflow, PyTorch, Kubernetes, GPU, LLM inference is a plus

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 $276,000-$414,000 annually.


Zone B:

The base salary range for this position is $262,000-$393,000 annually.

Zone C:

The base salary range for this position is $235,000-$352,000 annually.This position is eligible for equity in the form of RSUs.

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