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Ml Inference Jobs in Portland, OR (NOW HIRING)

... inference methods (e.g., Bayesian networks, structural causal models) Experience building or ... ML models in production systems Strong problem-solving skills and ability to work with complex ...

... causal inference methods (e.g., Bayesian networks, structural causal models) โ€ข Experience ... deploying ML models in production systems โ€ข Strong problem-solving skills and ability to work ...

... causal inference methods (e.g., Bayesian networks, structural causal models) โ€ข Experience ... deploying ML models in production systems โ€ข Strong problem-solving skills and ability to work ...

... causal inference methods (e.g., Bayesian networks, structural causal models) โ€ข Experience ... deploying ML models in production systems โ€ข Strong problem-solving skills and ability to work ...

... model inference services. You will learn and apply new techniques from open source packages and ... Work spans classical ML through LLM systems. You improve search and retrieval quality using real ...

Senior Performance Architect, Nemotron

Hillsboro, OR ยท 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 ...

AI Red Team Lead Engineer

Gresham, OR

$108K - $143K/yr

... on AI/ML systems, platforms, and integrations, in addition to traditional enterprise attack ... Training, evaluation, and inference pipelines * Data ingestion, labeling, and governance controls

Data Scientist I or II (MAD-BS-OR)

Hillsboro, OR ยท On-site +1

$121K - $167K/yr

... ML infrastructure * MLOps practices (CI/CD, monitoring, model versioning) * Knowledge of: * Signal processing or physics-based modeling * Graph-based reasoning or causal inference * Full software ...

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Ml Inference information

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$39.8K

$130.2K

$208.4K

How much do ml inference jobs pay per year?

As of Jun 11, 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 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.

Which 3 jobs will survive AI?

For ML Inference roles, jobs that require complex problem-solving, creativity, and emotional intelligence are more likely to persist, such as data scientists, AI ethics specialists, and machine learning engineers. These roles involve tasks that are difficult to automate and often require specialized skills, domain knowledge, and critical thinking. Continuous learning and expertise in AI tools and programming languages like Python or TensorFlow can also enhance job security in this field.

What engineers make $500,000?

Senior machine learning engineers with extensive experience, specialized skills in deep learning, and strong industry demand can earn $500,000 or more annually, especially in high-cost-of-living areas or within top tech companies. Achieving this level typically requires advanced degrees, certifications, and a proven track record of impactful projects.

What is a $900,000 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 requiring advanced skills in deep learning, data science, and experience with tools like TensorFlow or PyTorch. These positions usually involve leadership responsibilities, strategic planning, and may require multiple years of specialized experience or advanced degrees.

Is ML a high paying job?

Machine Learning (ML) inference roles are generally well-paid due to the specialized skills required, such as knowledge of algorithms, programming, and data analysis. Salaries vary based on experience, location, and industry, but they tend to be higher than average for tech positions. Advanced roles often require proficiency with tools like TensorFlow or PyTorch and may include certifications or advanced degrees.

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 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 cities near Portland, OR are hiring for Ml Inference jobs? Cities near Portland, OR with the most Ml Inference job openings:
Senior Software Engineer, AI Performance Analysis

Senior Software Engineer, AI Performance Analysis

NVIDIA

Hillsboro, OR โ€ข On-site

$152K/yr

Full-time

Posted 26 days ago


Job description

Job Summary:
NVIDIA is a world-class leader in AI workload optimization, and they are seeking a senior software engineer to automate and optimize performance analysis workflows for AI training and inference workloads. The role involves designing and building performance analysis tools, collaborating with engineers, and identifying performance bottlenecks in AI workloads.
Responsibilities:
โ€ข Design and build performance analysis tools and workflows for AI training and inference workloads.
โ€ข Understand how AI performance engineers work and translate their needs into scalable, intuitive tooling.
โ€ข Develop integrations between profiling infrastructure and AI frameworks and workflows.
โ€ข Collaborate with performance engineers, hardware architects, and software teams to ensure profiling capabilities align with real-world AI workloads.
โ€ข Identify performance bottlenecks in AI workloads and develop automated approaches to detect and diagnose them.
Qualifications:
Required:
โ€ข M.S., or PhD in Computer Science, Computer Engineering, or a related field (or equivalent experience). 6+ years of relevant work experience
โ€ข Deep knowledge of AI workloads, frameworks, and performance characteristics.
โ€ข Experience building tools, workflows, or infrastructure used by other engineers.
โ€ข Strong software development skills (Python, C++ preferred).
โ€ข Ability to translate user requirements into scalable tooling solutions.
โ€ข Up to date with AI-enabled tooling for software development and performance analysis.
โ€ข Strong interpersonal skills for understanding engineer difficulties and working across multi-functional teams.
Preferred:
โ€ข Experience profiling or optimizing AI training or inference pipelines at scale
โ€ข Background building developer tools or platforms for ML engineers
โ€ข Contributions to open-source AI tooling or frameworks
Company:
NVIDIA is a computing platform company operating at the intersection of graphics, HPC, and AI. Founded in 1993, the company is headquartered in Santa Clara, USA, with a team of 10001+ employees. The company is currently Late Stage.

Nvidia logo

About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

Year founded

1993