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Llm Training Jobs in Oregon (NOW HIRING)

Machine Learning Engineer 5 - Globalization

OR · On-site +1

$466K - $750K/yr

In this rare opportunity, you will design and build systems and infrastructure that make LLM training and inference faster, more scalable, and more reliable across a diverse global catalog and ...

Create and sponsor thought leadership, frameworks, blueprints for agentic AI and LLM adoption, and reusable assets (diagnostic tools, maturity models, training curricula, stakeholder playbooks)

This role is hands-on and delivery-oriented: you will ship production pipelines and services that support model training, real-time inference, and LLM applications using Claude-, GPT/Codex-, and ...

Utilize AI-assisted development tools (e.g., LLM coding assistants, code analysis tools) to enhance ... Familiarity with the AI/ML lifecycle including data preparation, model training, evaluation ...

Stay current with LLM developments, prompt engineering research, and the evolving Five9 AQM product ... Experience developing training materials or internal knowledge base documentation. Background in ...

Senior Software Engineer, Matrix Multiplication

OR · On-site +1

$122K - $161K/yr

Background in domain specific compiler and library solutions for LLM inference and training (e.g. FlashInfer, Flash Attention) * Expertise in inference engines like vLLM and SGLang * Expertise in ...

Technology Trainer - Anthropic Enablement

OR · On-site +1

$32.50 - $43.25/hr

... LLM platforms to teach and troubleshoot confidently. * Proven experience designing and delivering tiered training curricula (e.g., foundational/101 and advanced/201) to mixed technical and non ...

Senior Software Engineer, DGX Cloud AI Infrastructure

OR · On-site +1

$122K - $161K/yr

In this role you will set technical direction across communication libraries, model frameworks, and inference/training stacks to ensure state-of-the-art LLM workloads run efficiently and reliably at ...

... training and enablement on AI soluitons and supporting strategic initiatives that advance PCC's AI Solutions capabilities. Minimum Qualifications * AI Fluency: A solid understanding of AI/LLM ...

Software Engineer, DGX Cloud AI Infrastructure

OR · On-site +1

$172K - $204K/yr

Bring up, tune, and benchmark AI pre-training, post-training, and inference workloads using PyTorch, NeMo / Megatron, TensorRT-LLM, and adjacent NVIDIA AI software stacks. * Perform root-cause ...

Integrating networking capabilities into AI serving stacks such as vLLM, SGLang, and TensorRT-LLM ... training and inference patterns. * Proficiency in programming languages such as C, C++, Rust and ...

Research Scientist, World Models

OR · On-site +1

$155K - $269K/yr

LLM / VLM / VLA methods for scene understanding, reasoning, and control. * Generative scenario ... training and rendering pipelines. - Publish high-impact research at top conferences (CVPR, ECCV ...

... in LLM development. Demonstrated success in applying LLMs and other Foundation Models to real-world challenges, preferably with experience in post-training LLMs, including fine-tuning and ...

Design end-to-end ML pipelines including Data ingestion, feature engineering, model training ... Implement LLM-based systems with: * Tool-calling frameworks * Retrieval-Augmented Generation (RAG)

AI Engineer, Sr

Newberg, OR · On-site

$140 - $220/hr

Build and optimize LLM capabilities using retrieval augmented generation, model fine tuning, and ... Implement data pipelines and feature engineering processes to support reliable model training and ...

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Llm Training information

What is an LLM Training?

An LLM Training job involves developing, fine-tuning, and optimizing large language models (LLMs) to improve their performance and accuracy. This role typically includes data collection, preprocessing, model training, evaluation, and troubleshooting issues related to bias, efficiency, and scalability. Professionals in this field work with machine learning frameworks, large datasets, and computational resources to enhance AI capabilities. They may also collaborate with researchers, engineers, and product teams to deploy models for real-world applications.

What are the key skills and qualifications needed to thrive in the LLM Training position?

To excel in LLM Training, you need a strong background in machine learning, natural language processing (NLP), and computer science, often backed by an advanced degree in a related field. Experience with programming languages such as Python, frameworks like PyTorch or TensorFlow, and familiarity with data annotation tools are essential, along with knowledge of cloud platforms and distributed computing. Strong analytical thinking, effective communication, and the ability to collaborate across interdisciplinary teams set top candidates apart. These skills ensure high-quality model development, efficient project execution, and the ability to adapt to evolving AI technologies.

What types of teams or professionals does an LLM Training specialist typically collaborate with?

Professionals specializing in LLM Training often work closely with data engineers, software developers, domain experts, product managers, and quality assurance analysts. Collaboration is essential for collecting and preprocessing training data, integrating models into products, and ensuring outputs meet business and user requirements. These roles frequently participate in agile project workflows, contribute to cross-functional team meetings, and collaborate on continuous model improvements. Engaging with diverse teams expands your understanding of product goals and helps you deliver robust and reliable language models that align with organizational objectives.

Is it possible to train Llm Training?

Training large language models (LLMs) is possible but requires significant computational resources, expertise in machine learning, and access to large datasets. It typically involves using specialized hardware like GPUs or TPUs and knowledge of frameworks such as TensorFlow or PyTorch. Many organizations opt to fine-tune pre-trained models rather than train from scratch due to the high costs and complexity involved.

What are the most commonly searched types of Llm Training jobs in Oregon?

The most popular types of Llm Training jobs in Oregon are:

What job categories do people searching Llm Training jobs in Oregon look for?

The top searched job categories for Llm Training jobs in Oregon are:

What cities in Oregon are hiring for Llm Training jobs?

Cities in Oregon with the most Llm Training job openings:

Infographic showing various Llm Training job openings in Oregon as of August 2026, with employment types broken down into 1% As Needed, 79% Full Time, 19% Part Time, and 1% Contract. Highlights an 89% Physical, 1% Hybrid, and 10% Remote job distribution.

Machine Learning Engineer 5 - Globalization

Netflix

OR • On-site, Remote

$466K - $750K/yr

Full-time

Medical, Life, Retirement, PTO

Re-posted 25 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. The Globalization Data Science and Engineering team is at the forefront of removing language barriers and providing a stellar member experience to all our members regardless of their language preferences. We are responsible for the translation and cultural adaptation of all aspects of member interaction, including beautiful localized user interfaces, subtitles, and dubbing of award-winning Netflix originals.

We are looking for an experienced Machine Learning Engineer with deep expertise in training and inference efficiency for Large Language Models (LLMs), Multimodal LLMs, and other media ML models. In this rare opportunity, you will design and build systems and infrastructure that make LLM training and inference faster, more scalable, and more reliable across a diverse global catalog and workload. You will partner with a talented cross-functional team of scientists, engineers, product managers, and domain experts to deliver business impact through efficient, production-ready ML solutions.

Responsibilities Design and build scalable training and inference systems for LLMs, Multimodal LLMs, and other media ML models. Optimize end-to-end training: data pipelines (streaming, sharding, bucketing), distributed training (parallelism strategies), and mixed precision. Optimize inference and serving: KV cache, batching, quantization, and long-context handling.

Scale model training and inference into robust, performant systems integrated into Netflix workflows. Act as a technical thought leader for training and inference efficiency, driving initiatives that significantly improve scalability, latency, and reliability. Mentor and uplevel other engineers and scientists in large-scale ML systems and performance engineering.

About you Extensive experience in ML engineering for large, production-grade systems using LLMs, Multimodal LLMs, and other media ML models. Deep hands-on expertise in training optimization: high-throughput data loading (streaming, sharding, bucketing); distributed training (parallelism strategies); GPU/accelerator optimization. Strong experience in inference optimization: KV cache design and optimization; batching and scheduling for high-throughput, low-latency serving; quantization and/or model compression.

Proficient with PyTorch and solid software engineering fundamentals (testing, observability, performance profiling). Proven track record of leading ML initiatives and partnering with stakeholders to define and execute impactful roadmaps. Exceptional communication and collaboration skills; comfortable with ambiguity and high ownership.

Netflix culture resonates with you. 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


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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