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Machine Learning Quantum Computing Jobs in Oregon

Senior AI Engineer - SFL Scientific

Portland, OR · On-site

$110K - $152K/yr

Work with clients to design, develop, and deploy new architectures to support machine learning ... using cloud computing or on-prem technologies * Design and lead development on scalable, high ...

OR

$193K/yr

Meta is building the next generation of AI infrastructure to power large-scale machine learning ... computing network environments Preferred Qualifications: * Demonstrated ongoing AI skill ...

Python Tutor

Eugene, OR · Remote

$18 - $40/hr

Emphasizes readable, maintainable code and connects Python to machine learning, web scraping, scientific computing, and DevOps applications. * Curriculum Awareness & Adaptive Instruction: Familiar ...

Python Tutor

Portland, OR · Remote

$18 - $40/hr

Emphasizes readable, maintainable code and connects Python to machine learning, web scraping, scientific computing, and DevOps applications. * Curriculum Awareness & Adaptive Instruction: Familiar ...

Python Tutor

OR · Remote

$18 - $40/hr

Emphasizes readable, maintainable code and connects Python to machine learning, web scraping, scientific computing, and DevOps applications. * Curriculum Awareness & Adaptive Instruction: Familiar ...

... computing frameworks, specifically Apache Spark/Databricks; ability to adapt code base to also run ... Strong understanding of various machine learning algorithms, including supervised and unsupervised ...

... of computing. Collaborating with cross-functional teams, you will develop methods and tools to ... Extract insights from structured and unstructured data using machine learning, coding techniques ...

... of computing. Collaborating with cross-functional teams, you will develop methods and tools to ... Extract insights from structured and unstructured data using machine learning, coding techniques ...

... of computing. Collaborating with cross-functional teams, you will develop methods and tools to ... Extract insights from structured and unstructured data using machine learning, coding techniques ...

... of computing. Collaborating with cross-functional teams, you will develop methods and tools to ... Extract insights from structured and unstructured data using machine learning, coding techniques ...

... machine learning research applications. * Curriculum Awareness & Adaptive Instruction: Familiar ... Adapts instruction using R or Python statistical computing, research paper examples, and proof ...

Showing results 21-40

Machine Learning Quantum Computing information

What is machine learning quantum computing?

Machine Learning Quantum Computing is an interdisciplinary field that combines principles of quantum computing with machine learning techniques. It aims to leverage the computational power of quantum computers to enhance the performance of machine learning algorithms, potentially solving complex problems more efficiently than classical computers. This area includes developing quantum algorithms for tasks such as classification, clustering, and optimization, as well as using machine learning to improve quantum hardware and error correction. Researchers expect that, as quantum hardware matures, this field could revolutionize data analysis, cryptography, and scientific discovery.

What are the key skills and qualifications needed to thrive as a machine learning quantum computing specialist?

To thrive in Machine Learning Quantum Computing, you need strong foundations in quantum mechanics, linear algebra, and advanced machine learning concepts, typically supported by a degree in physics, computer science, or a related field. Familiarity with quantum programming languages (such as Qiskit or Cirq), cloud-based quantum platforms, and proficiency in Python are usually required, alongside experience with relevant certifications or coursework. Strong problem-solving skills, adaptability, and effective collaboration are vital soft skills in this interdisciplinary field. These competencies are crucial for driving innovation and bridging the gap between quantum computing and practical machine learning applications.

How do professionals in machine learning quantum computing typically collaborate with interdisciplinary teams?

Professionals in Machine Learning Quantum Computing often work closely with experts in physics, computer science, and engineering. Collaboration usually involves translating quantum concepts for machine learning specialists and vice versa, ensuring that algorithms are both theoretically sound and practically implementable on quantum hardware. Regular meetings, code reviews, and knowledge-sharing sessions are standard, as interdisciplinary insight is crucial for advancing research and developing scalable solutions. Effective communication and a willingness to learn from other domains are essential for success in these teams.

What is the difference between Machine Learning Quantum Computing vs Data Scientist?

AspectMachine Learning Quantum ComputingData Scientist
Required CredentialsAdvanced degrees in quantum computing, machine learning, or related fieldsDegree in data science, statistics, or computer science
Work EnvironmentResearch labs, tech companies focusing on quantum tech, academiaBusiness environments, tech companies, consulting firms
Industry UsageEmerging quantum tech industry, research institutionsFinance, healthcare, marketing, e-commerce
Common Search/ComparisonQuantum algorithms, quantum machine learningData analysis, predictive modeling

Machine Learning Quantum Computing specialists focus on developing algorithms that leverage quantum mechanics to enhance machine learning tasks, often requiring advanced knowledge of quantum physics. Data Scientists analyze and interpret large datasets using traditional machine learning techniques. While both roles involve machine learning, the former emphasizes quantum computing applications, whereas the latter centers on data analysis in conventional computing environments.

What are popular job titles related to Machine Learning Quantum Computing jobs in Oregon?

For Machine Learning Quantum Computing jobs in Oregon, the most frequently searched job titles are:

What job categories do people searching Machine Learning Quantum Computing jobs in Oregon look for?

The top searched job categories for Machine Learning Quantum Computing jobs in Oregon are:

What cities in Oregon are hiring for Machine Learning Quantum Computing jobs?

Cities in Oregon with the most Machine Learning Quantum Computing job openings:

Software Engineer 5 - Training Platform, AI Platform

Netflix

OR • On-site, Remote

Full-time

Medical, Life, Retirement, PTO

Re-posted 3 days ago


Netflix rating

5.8

Company rating: 5.8 out of 10

Based on 15 frontline employees who took The Breakroom Quiz

72nd of 78 rated media


Job description

At Netflix, our mission is to entertain the world. Together, we are writing the next episode - pushing the boundaries of storytelling, global fandom and making the unimaginable a reality. We are a dream team obsessed with the uncomfortable excitement of discovering what happens when you merge creativity, intuition and cutting-edge technology.

Come be a part of what's next. Netflix is the world's leading streaming entertainment service, with 278 million paid members in over 190 countries, enjoying TV series, feature films, and games across numerous genres and languages. Members can watch or play as much as they want, anytime, anywhere, on any internet-connected screen.

Machine Learning/Artificial Intelligence powers innovation in all areas of the business, from helping members choose the right title for them through personalization, to better understanding our audience and our content slate, to optimizing our payment processing and other revenue-focused initiatives. Building highly scalable and differentiated ML infrastructure is key to accelerating this innovation. The Opportunity We are looking for a senior engineer with deep expertise in distributed model training and the systems required to operate it at scale.

You will help shape the architecture of our training platform, improve performance and reliability for large training jobs, and build intuitive platform experiences for ML engineers. Our infrastructure is built on Kubernetes, Ray clusters, and PyTorch distributed training primitives. This role requires strong technical depth, sound engineering judgment, and the ability to influence across teams.

You will partner closely with ML engineers, researchers, infrastructure teams, and platform stakeholders to identify needs, lead technical discussions, drive alignment, and deliver high-impact capabilities. charter is to maximize the business impact of all AI use cases at Netflix through highly reliable and flexible AI tooling and infrastructure that supports key product functions such as personalized recommendations, studio algorithms, virtual productions, growth intelligence, and content demand modeling among others. In this role you will get to: Design and build the platform that powers large-scale machine learning model training, fine-tuning, model transformation and evaluations workflows and use cases from the entire company Co-design and optimize the systems and models to scale up and increase the cost-effectiveness of machine learning model training Design easy-to-use APIs and interfaces for experienced ML practitioners, as well as non-experts to easy access the training platform Minimum Job Qualifications Design, build, and operate platform infrastructure, libraries, and SDKs for large-scale model training.

Enable reliable and efficient training workflows for foundation models and generative AI models of all sizes. Diagnose and optimize the performance of large distributed training jobs, including GPU utilization, memory efficiency, communication overhead, data loading, checkpointing, fault tolerance, and cluster utilization. Experience with cloud computing providers, preferably AWS Comfortable with ambiguity and working across multiple layers of the tech stack to execute on both 0-to-1 and 1-to-100 projects Adopt and promote best practices in operations, including observability, logging, reporting, and on-call processes to ensure engineering excellence.

Excellent written and verbal communication skills Comfortable working in a team with peers and partners distributed across (US) geographies & time zones. Preferred Qualifications Understand modern and real-world Machine Learning model development workflows and experience partnering closely with ML modeling engineers. Lead technical design reviews, facilitate cross-functional discussions, communicate tradeoffs clearly, and align stakeholders on platform direction and execution priorities.

Familiarity with cloud-based AI/ML services (e.g., SageMaker, Bedrock, Databricks, OpenAI, etc.) Familiarity with distributed training performance analysis tools and techniques, such as PyTorch Profiler, NVIDIA Nsight Systems, GPU telemetry, communication profiling, or cluster-level utilization analysis. Experience with large-scale distributed training and different parallelism techniques for scaling up training, such as FSDP and tensor/pipeline parallelism Expertise in the area of Generative AI, specifically when it comes to training foundation models, fine-tuning them, and distilling them to smaller models Generally, our compensation structure consists solely of an annual salary; we do not have bonuses. You choose each year how much of your compensation you want in salary versus stock options

To determine your personal top of market compensation, we rely on market indicators and consider your specific job family, background, skills, and experience to determine your compensation in the market range. The range for this role is $466,000.00 - $750,000.00. This compensation range will vary based on location

Netflix provides comprehensive benefits including Health Plans, Mental Health support, a 401(k) Retirement Plan with employer match, Stock Option Program, Disability Programs, Health Savings and Flexible Spending Accounts, Family-forming benefits, and Life and Serious Injury Benefits. We also offer paid leave of absence programs. Full-time hourly employees accrue 35 days annually for paid time off to be used for vacation, holidays, and sick paid time off.

Full-time salaried employees are immediately entitled to flexible time off. See more details about our Benefits here. Netflix is a unique culture and environment.

Learn more here. Inclusion is a Netflix value and we strive to host a meaningful interview experience for all candidates. If you want an accommodation/adjustment for a disability or any other reason during the hiring process, please send a request to your recruiting partner.

We are an equal-opportunity employer and celebrate diversity, recognizing that diversity builds stronger teams. We approach diversity and inclusion seriously and thoughtfully. We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service.

Job is open for no less than 7 days and will be removed when the position is filled.


What Netflix employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


Netflix logo

About Netflix

Sourced by ZipRecruiter

Netflix is the world's leading streaming entertainment service with 222 million paid memberships in over 190 countries enjoying TV series, documentaries, feature films and mobile games across a wide variety of genres and languages. Members can watch as much as they want, anytime, anywhere, on any Internet-connected screen. Members can play, pause and resume watching, all without commercials or commitments.

Industry

Arts, entertainment, and recreation

Company size

5,001 - 10,000 Employees

Headquarters location

Los Gatos, CA, US

Year founded

1997