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Ml Inference Jobs in Portland, OR (NOW HIRING)

RevSpring Inc

Data Architect (Data Platform)

Portland, OR

$67.50 - $87/hr

Define and evolve data architectures that support AI/ML workloads, including curated training datasets, feature stores, and scalable pipelines for batch and real-time inference * Define and evolve ...

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All JobsMl Inference JobsMl Inference Jobs in Portland, OR

Ml Inference information

See Portland, OR salary details

$39.8K

$130.2K

$208.4K

How much do ml inference jobs pay per year?

As of Jul 20, 2026, the average yearly pay for ml inference in Portland, OR is $130,165.00, according to ZipRecruiter salary data. Most workers in this role earn between $104,500.00 and $144,200.00 per year, depending on experience, location, and employer.

What is a $900000 AI job?

A $900,000 AI job typically refers to high-level roles in artificial intelligence, such as senior machine learning engineers or AI research directors, often involving advanced skills in deep learning, data modeling, and programming with tools like Python and TensorFlow. These positions usually require extensive experience, specialized knowledge, and may include leadership responsibilities or strategic decision-making.

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 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 engineer makes $500,000 a year?

Senior machine learning engineers with extensive experience, advanced skills in deep learning, and expertise in deploying large-scale models can earn salaries approaching or exceeding $500,000 annually, especially in high-cost-of-living areas or top tech companies. Compensation often includes base salary, bonuses, and stock options, reflecting their specialized knowledge and impact on product development.

Which 3 jobs will survive AI?

Jobs involving Ml Inference, such as data scientists, machine learning engineers, and AI system architects, are likely to persist as they require specialized expertise in developing, deploying, and maintaining AI models. These roles demand critical thinking, domain knowledge, and skills in programming and data analysis that are less easily automated. Continuous learning and staying updated with AI tools and frameworks are essential for these professions to remain relevant.

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.

Will MLE be replaced by AI?

Machine Learning Engineers (MLEs) design, develop, and optimize AI models and systems. While AI automation tools can assist with certain tasks, MLEs are essential for building, tuning, and maintaining complex models, making complete replacement unlikely in the near term. Their expertise in data handling, model deployment, and system integration remains critical in AI development environments.

What are the key skills and qualifications needed to thrive in ML Inference, and why are they important?

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 popular job titles related to Ml Inference jobs in Portland, OR? For Ml Inference jobs in Portland, OR, the most frequently searched job titles are:
What job categories do people searching Ml Inference jobs in Portland, OR look for? The top searched job categories for Ml Inference jobs in Portland, OR are:
What cities near Portland, OR are hiring for Ml Inference jobs? Cities near Portland, OR with the most Ml Inference job openings:
Ml Inference jobs near you
Infographic showing various Ml Inference job openings in Portland, OR as of July 2026, with employment types broken down into 81% Full Time, 18% Part Time, and 1% Contract. Highlights an 71% Physical, 2% Hybrid, and 27% Remote job distribution, with an average salary of $130,165 per year, or $62.6 per hour.
Principal Engineer: XeSS and Neural Graphics

Principal Engineer: XeSS and Neural Graphics

Intel

Hillsboro, OR • On-site

$255K - $361K/yr

Full-time

Medical, Retirement, PTO

Re-posted 21 days ago

Intel rating

8.7

Company rating: 8.7 out of 10

Based on 147 frontline employees who took The Breakroom Quiz

11th of 143 rated electronics manufacturers

Job description

Job Details:Job Description: Drive Intel's XeSS and related AI-based graphics technologies for Client Graphics, with direct impact across XeSS Super Resolution, XeSS Frame Generation, Neural Rendering, and next-generation AI rendering capabilities.In this role, you will help shape technical direction, drive execution across teams, and contribute to the future of AI-based graphics at Intel. You will work across research, software, hardware architecture, validation, and ecosystem teams to bring new AI graphics technologies from concept to product.You will play a key role in end-to-end development across model design, datasets, training, visual quality, performance optimization, and product integration. You will also help guide how modern AI model architectures are applied to future graphics workloads.Qualifications:Minimum QualificationsBachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, Applied Mathematics, or related field, with 12+ years of experience, or Master's degree with 10+ years of experience.Strong expertise in AI/ML for real-time graphics, imaging, or video, such as super resolution, frame generation, denoising, reconstruction, optical flow, or related AI rendering workloads.Proven experience driving AI technology from research to shipped product, including model architecture, datasets, training, evaluation, optimization, and deployment.Strong understanding of GPU architecture, performance, memory, latency, and hardware-aware optimization.Demonstrated leadership across cross-functional technical teams spanning research, software, and hardware.Preferred QualificationsExperience with XeSS, Neural Rendering, or adjacent AI-based graphics technologies.Good understanding of modern AI model architectures, such as LLMs, Vision Transformers, Diffusion, and related architectures.Experience with high-performance GPU compute, inference kernels, or production AI deployment.Experience with dataset capture, processing, and training infrastructure for graphics AI models.Experience with SDK, API, or cross-platform AI productization.Experience influencing future GPU, NPU, or accelerator features based on AI workload analysis.Job Type:Experienced HireShift:Shift 1 (United States of America)Primary Location: US, Oregon, HillsboroAdditional Locations:Business group:At the Data Center Group (DCG), we're committed to delivering exceptional products and delighting our customers. We offer both broad-market Xeon-based solutions and custom x86-based products, ensuring tailored innovation for diverse needs across general-purpose compute, web services, HPC, and AI-accelerated systems. Our charter encompasses defining business strategy and roadmaps, product management, developing ecosystems and business opportunities, delivering strong financial performance, and reinvigorating x86 leadership. Join us as we transform the data center segment through workload driven leadership products and close collaboration with our partners.Posting Statement:All qualified applicants will receive consideration for employment without regard to race, color, religion, religious creed, sex, national origin, ancestry, age, physical or mental disability, medical condition, genetic information, military and veteran status, marital status, pregnancy, gender, gender expression, gender identity, sexual orientation, or any other characteristic protected by local law, regulation, or ordinance.Position of TrustThis role is a Position of Trust. Should you accept this position, you must consent to and pass an extended Background Investigation, which includes (subject to country law), extended education, SEC sanctions, and additional criminal and civil checks. For internals, this investigation may or may not be completed prior to starting the position. For additional questions, please contact your Recruiter.Benefits

We offer a total compensation package that ranks among the best in the industry. It consists of competitive pay, stock bonuses, and benefit programs which include health, retirement, and vacation. Find out more about the benefits of working at Intel.

Annual Salary Range for jobs which could be performed in the US: $255,850.00-361,200.00 USDThe range displayed on this job posting reflects the minimum and maximum target compensation for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific compensation range for your preferred location during the hiring process.

Work Model for this Role

This role will be eligible for our hybrid work model which allows employees to split their time between working on-site at their assigned Intel site and off-site. * Job posting details (such as work model, location or time type) are subject to change.

*

ADDITIONAL INFORMATION: Intel is committed to Responsible Business Alliance (RBA) compliance and ethical hiring practices. We do not charge any fees during our hiring process. Candidates should never be required to pay recruitment fees, medical examination fees, or any other charges as a condition of employment. If you are asked to pay any fees during our hiring process, please report this immediately to your recruiter.

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About Intel

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Intel strives to make every facet of semiconductor manufacturing state-of-the-art -- from semiconductor process development and manufacturing, through yield improvement to packaging, final test and optimization, and world class Supply Chain and facilities support. Employees in the Technology and Manufacturing Group are part of a worldwide network of design, development, manufacturing, and assembly/test facilities, all focused on utilizing the power of Moore's Law to bring smart, connected devices to every person on Earth

Industry

Manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

Year founded

1968

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