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Ml Inference Jobs in Oregon (NOW HIRING)

Nvidia

OR · On-site

$122K - $161K/yr

... with ML/DL systems development preferable * Strong experience in developing or using deep learning frameworks (e.g. PyTorch, JAX, TensorFlow, ONNX, etc) and ideally inference engines and runtimes ...

Netflix

OR · On-site

$466K - $750K/yr

Data Science and Engineering ('DSE') at Netflix is aimed at using data, analytics, causal inference, machine learning (ML), and sciences to improve various aspects of our business. The AI initiative ...

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 ...

WEKA

OR

Familiarity with LLM deployment stacks, GPU compute, and ML frameworks ( PyTorch, TensorFlow, JAX ). * AI Lifecycle Expertise: Experience across the software stack, including fine-tuning, inference ...

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 ...

iHerb

OR

$114K - $137K/yr

Designs scalable data pipelines optimized for ML workloads, such as batch, streaming, and real-time inference use cases. * Establishes MLOps standards, coding practices, and automation patterns that ...

phData

OR

Own and drive end-to-end solution design and delivery of AI/ML and data solutions for strategic client accounts, from model inference, retraining, and monitoring through to production operations.

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 ...

Instacart

OR

$91K - $124K/yr

The team has strong ML infrastructure and MLOps support, including Delta/DBT-Spark data pipelines ... Strong foundation in causal inference, counterfactual reasoning, and training data bias mitigation.

Cotiviti

$125K - $172K/yr

Proven track record leading end-to-end ML projects, from problem framing through production impact. * Strong experimentation discipline: A/B testing, causal inference, metric design, and opportunity ...

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Ml Inference information

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.
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Ml Inference jobs near you
Modeling Engineer 3 (CFD, Thermal, AI/ML)

Modeling Engineer 3 (CFD, Thermal, AI/ML)

Lam Research Corporation

Tualatin, OR • On-site

Full-time

Posted 26 days ago

Lam Research rating

8.7

Company rating: 8.7 out of 10

Based on 45 frontline employees who took The Breakroom Quiz

47th of 430 rated machine equipment manufacturers

Job description

The group you'll be a part of
In the Global Products Group, we are dedicated to excellence in the design and engineering of Lam's etch and deposition products. We drive innovation to ensure our cutting-edge solutions are helping to solve the biggest challenges in the semiconductor industry.
The impact you'll make
We move atoms that move the world.
At Lam Research, we create equipment that allows chipmakers to build device features more than 1,000 times smaller than a grain of sand. This tiny scale has a huge impact. Virtually every leading-edge chip inside the electronic products you use every day (TVs, smartphones, laptops, cars-even medical devices) has been made using our equipment.
As one of the world's most trusted suppliers in the semiconductor equipment industry, we're transforming technology. Our equipment places atoms so precisely that nearly every chip today is made using our innovations.
To build a prosperous career, start with an atom.
Should you choose to walk the path historically driven by Moore's law, your primary job function will involve cutting edge R&D activities in the Semiconductor Equipment Industry. If solving challenges no one has faced before or attempted are of interest to you, then Lam Research is the company for you.
What you'll do
  • Developing physics-based models for Thermal/CFD/Chemistry applications for components in semiconductor capital equipment industry. Experience in commercial software like ANSYS Fluent, Star CCM+, or COMSOL, etc., is highly desirable.
  • Utilizing DOE, Optimization, and statistical methods and data driven modeling to correlate Simulation data to experimental data.
  • Predict, measure, and analyze the experimental data for uncertainty Quantification & propagation, sensitivity analysis, statistical inference for model calibration, decision making under uncertainty.
  • Multi-scale modeling from nano, meso to macro levels
  • Provide design improvements of in-service tools based upon quantitative field measured failure data and less quantitative quality metrics as measured by Lam Research.
  • Provide written reports and oral presentation of results to design teams and management.
  • Work directly with mechanical, electrical, process and software engineers to define design requirements, goals and objectives of design, CIP, testing and simulation plans.
  • Strong written and oral communication. Self-starter to start own initiatives and projects for continuous improvement in capabilities and design.
  • Put your running shoes on: In this job you'll work in a highly dynamic and rapidly changing environment within a team of interdisciplinary experts driving to solutions to the most challenging business needs.

Who we're looking for
  • PhD in Mechanical Engineering or closely related field with strong emphasis in Computational Fluid Dynamics, Heat transfer, Chemistry, or related fields; and 0-3 years professional experience.
  • Strong ability and understanding of AI/ML concepts and hybrid physics-based AI/ML modeling software.
  • Coding ability to supplement commercial software for specific applications as needs arise.
  • Ability to effectively communicate and build relationships to interact, inform, influence, and communicate with key stakeholders at all levels across the company.
  • Strong critical thinking skills demonstrated through problem-solving, attention to detail and innovation.
  • Strong analytical skills demonstrated through First Principles Thinking, statistical Analysis and Physics-based Insights
  • This is a graduate eligible position.

Preferred qualifications
  • Preferred knowledge of chemistry, semiconductor metrology methods, and hardware designs in a vacuum environment is also a plus.
  • Ability to work within a team to own and design concepts and drive design decisions.
  • Established skills in building AI/ML models using simulation data.
  • Experience with machine learning algorithms and tools (e.g., TensorFlow, PyTorch, Scikit Learn etc.) and deep learning.
  • General understanding of uncertainty quantification, Bayesian optimization and probabilistic machine learning is required.

Our commitment
We believe it is important for every person to feel valued, included, and empowered to achieve their full potential. By bringing unique individuals and viewpoints together, we achieve extraordinary results.
Lam Research ("Lam" or the "Company") is an equal opportunity employer. Lam is committed to and reaffirms support of equal opportunity in employment and non-discrimination in employment policies, practices and procedures on the basis of race, religious creed, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex (including pregnancy, childbirth and related medical conditions), gender, gender identity, gender expression, age, sexual orientation, or military and veteran status or any other category protected by applicable federal, state, or local laws. It is the Company's intention to comply with all applicable laws and regulations. Company policy prohibits unlawful discrimination against applicants or employees.
Lam offers a variety of work location models based on the needs of each role. Our hybrid roles combine the benefits of on-site collaboration with colleagues and the flexibility to work remotely and fall into two categories - On-site Flex and Virtual Flex. 'On-site Flex' you'll work 3+ days per week on-site at a Lam or customer/supplier location, with the opportunity to work remotely for the balance of the week. 'Virtual Flex' you'll work 1-2 days per week on-site at a Lam or customer/supplier location, and remotely the rest of the time.
IND123 #LI-CW1 #LI-Onsite
Our Perks and Benefits
At Lam, our people make amazing things possible. That's why we invest in you throughout the phases of your life with a comprehensive set of outstanding benefits.

What Lam Research employees say

Pay

Benefits

Hours and flexibility

Workplace

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About Lam Research

Sourced by ZipRecruiter

Lam Research designs and builds products for semiconductor manufacturing, including equipment for thin film deposition, plasma etch, photoresist strip, and wafer cleaning processes.

Industry

Manufacturing

Company size

10,000+ Employees

Headquarters location

Fremont, CA, US

Year founded

1980

Social media

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