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Ml Inference Jobs in Portland, OR (NOW HIRING)

Cisco

Applied AI Scientist

Hillsboro, OR

Explore and evaluate new AI/ML techniques, tools, and methodologies, applying relevant innovations ... and inference efficiency to minimize cost and latency while preserving accuracy. * MLOps ...

New

Cisco

Applied AI Scientist

Portland, OR

Explore and evaluate new AI/ML techniques, tools, and methodologies, applying relevant innovations ... and inference efficiency to minimize cost and latency while preserving accuracy. * MLOps ...

New

Nvidia

Senior Performance Architect, Nemotron

Hillsboro, OR · On-site

$181K/yr

Solid understanding of ML fundamentals, model parallelism and inference serving techniques. * Proficiency in Python (and optionally C++) for simulator design and data analysis. * 3+ years of hands-on ...

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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 16, 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.
Embedded CPU Engineer, Platform Architecture

Embedded CPU Engineer, Platform Architecture

Apple

Beaverton, OR

Full-time

Re-posted 7 days ago

Apple rating

8.1

Company rating: 8.1 out of 10

Based on 670 frontline employees who took The Breakroom Quiz

5th of 30 rated technology retailers

Job description

We are seeking a highly motivated and innovative Embedded CPU Engineer to join the Platform Architecture team. In this role, you will drive performance and efficiency optimization and architectural feature exploration for Apple’s embedded CPUs that power critical functions across Apple's product line.
Description
As an Embedded CPU Engineer, you will help define CPUs that are specifically designed for running embedded applications across iPhone, iPad, Mac, and other Apple products. Your focus will be on understanding the unique constraints and opportunities of varied embedded use cases and translating those insights into improvements for both the software stack as well as the hardware including the CPU and its surrounding subsystem.
You will be responsible for deep-dive performance analysis of embedded workloads, identifying bottlenecks in existing microarchitectures, and proposing optimization strategies that balance performance, power efficiency, and area. Working closely with algorithm teams, software engineers, and CPU designers, you will explore ISA extensions, microarchitecture enhancements, and system-level optimizations tailored to embedded use cases.
This role requires some background in software profiling, performance modeling, and simulation environments. You will use and develop analysis tools and infrastructure to enable data-driven architectural decisions, create and analyze both real workloads and benchmarks representative of embedded workloads, and iterate with design teams to ensure ideas are implementable within power, timing, and area constraints.","responsibilities":"Analyze performance characteristics of embedded workloads including real-time processing, audio DSP, always-on scenarios, and embedded ML inference
Collaborate with system architecture and software teams to understand use case requirements that could be unique for each environment
Translate findings into actionable improvements to our designs and software
Work with CPU design team to implement proposed improvements while balancing tradeoffs for power, timing and area
Provide feedback into and help develop performance models, simulators, and analysis tools used to support architectural exploration
Preferred Qualifications
MS or PhD in Electrical Engineering, Computer Engineering, or Computer Science
10+ years of industry experience in CPU architecture or performance analysis
Expertise in CPU microarchitecture in one or more of the following areas: branch prediction, prefetching, pipeline optimization, datapath, memory hierarchy
Experience in one or more of the following areas: embedded ML workloads and inference engines, SIMD/vector architectures for signal processing or ML, or compiler infrastructure and toolchain development for embedded workloads
Experience with real-time operating systems and embedded software constraints
Understanding of: power-performance trade-offs in CPU designs, system-level power management, and low-power design techniques
Strong communication and collaboration skills across hardware and software teams
Experience taking architectural ideas from concept through implementation
Minimum Qualifications
BS in Electrical Engineering, Computer Engineering, Computer Science, or similar
CPU architecture or microarchitecture experience
Experience with performance simulation environments, and performance analysis or optimization of workloads
Experience with one or more of the following ISAs: ARM, RISC-V, x86
Experience in C, C++, or similar programming languages
Experience with scripting languages such as Python or Perl for analysis and automation

What Apple employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

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About Apple

Sourced by ZipRecruiter

Imagine what you could do here! At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Dynamic, intelligent people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same real passion for innovation that goes into our products also applies to our practices strengthening our dedication to leave the world better than we found it.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Cupertino, CA, US

Year founded

1976

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