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Machine Learning Trainer Jobs in Oregon (NOW HIRING)

The Role We are seeking a Machine Learning Scientist to lead the research and development of Large ... training pipelines. * Pragmatic Builder: Ability to prioritize impact by deciding when to use ...

OR · On-site

$122.40K - $161.30K/yr

... both training and inference pipelines. * Collaborate closely with AI researchers, HW and SW ... Experience with machine learning, especially agentic systems, applied to systems problems. Your ...

OR · Hybrid

We are now looking for a Senior Machine Learning Applications and Compiler Engineer! NVIDIA is ... Experience with large-scale AI distributed inference or training systems, including performance ...

AI Data Engineer Senior Consultant

Portland, OR · On-site

$121.40K - $145.80K/yr

... machine learning training and real-time inference, including online and offline consistency, caching, latency targets, and backfills • Implement privacy, access, quality, lineage, monitoring ...

New

AI Data Engineer Senior Consultant

Portland, OR · On-site +1

$112.40K - $152.70K/yr

Deliver governed datasets and feature engineering and serving patterns for machine learning training and real-time inference, including online and offline consistency, caching, latency targets, and ...

Experience with machine learning frameworks and their internals (e.g. PyTorch, TensorFlow, scikit ... Understanding of deep learning training in distributed contexts: multi-GPU, multi-node, synchronous ...

OR

$466K - $750K/yr

Experience building machine learning models or LLMs * Experience scaling and optimizing the training and serving of machine learning models * Experience with machine learning libraries TensorFlow ...

OR · On-site

$466K - $750K/yr

Experience building machine learning models or LLMs Experience scaling and optimizing the training and serving of machine learning models Experience with machine learning libraries TensorFlow ...

OR

$122.40K - $161.30K/yr

Experience with machine learning frameworks and their internals (e.g. PyTorch, TensorFlow, scikit ... Understanding of deep learning training in distributed contexts: multi-GPU, multi-node, synchronous ...

Overview LMI is seeking a Machine Learning Operations Engineer (ML Ops Engineer) to support the ... model training and analysis. * Support CI/CD pipelines tailored for ML model development and ...

Leading sales, solution design, and delivery for artificial intelligence, machine learning ... and training; licensure and certifications; and other business and organizational needs. The ...

OR

$466K - $750K/yr

Applied Machine Learning Research at Netflix drives various aspects of our business, including ... experience in post-training LLMs, including fine-tuning and distillation. Strong software ...

MAIN TASKS & RESPONSIBILITIES Machine Learning Model Updates: * Update training and test model databases with new or amended synthetic textual and image data. * Modify and refine machine learning ...

OR

$466K - $750K/yr

Applied Machine Learning Research at Netflix drives various aspects of our business, including ... Hands-on experience in distributed training, reinforcement learning-based training of LLMs ...

OR · On-site

MAIN TASKS & RESPONSIBILITIES Machine Learning Model Updates: * Update training and test model databases with new or amended synthetic textual and image data. * Modify and refine machine learning ...

OR

$16 - $20.75/hr

MAIN TASKS & RESPONSIBILITIES Machine Learning Model Updates: * Update training and test model databases with new or amended synthetic textual and image data. * Modify and refine machine learning ...

PhD or Masters in Computer Science, Statistics, or a related field Expertise in machine learning algorithms and frameworks, with hands-on experience in training, tuning, and deploying models in ...

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Showing results 1-20

Machine Learning Trainer information

See Oregon salary details

$29.6K

$92.3K

$118.9K

How much do machine learning trainer jobs pay per year?

As of May 29, 2026, the average yearly pay for machine learning trainer in Oregon is $92,327.00, according to ZipRecruiter salary data. Most workers in this role earn between $63,400.00 and $117,400.00 per year, depending on experience, location, and employer.

What is a Machine Learning Trainer job?

A Machine Learning Trainer is responsible for preparing and curating datasets, fine-tuning machine learning models, and optimizing algorithms for accuracy and efficiency. They work closely with data scientists and engineers to improve model performance and ensure high-quality training data. This role involves tasks like labeling data, selecting features, and implementing preprocessing techniques. Additionally, they may develop training methodologies and evaluate models using various metrics to enhance their effectiveness.

What are the key skills and qualifications needed to thrive in the Machine Learning Trainer position, and why are they important?

To thrive as a Machine Learning Trainer, you need a solid background in computer science, statistics, and machine learning concepts, often supported by relevant academic degrees and industry experience. Familiarity with programming languages like Python, frameworks such as TensorFlow or PyTorch, and certifications like TensorFlow Developer or AWS Machine Learning are valuable assets. Excellent communication, patience, and adaptability allow trainers to effectively convey complex concepts to diverse learners. These skills ensure effective teaching, learner engagement, and successful knowledge transfer in a rapidly evolving technological landscape.

What are the typical challenges faced by a Machine Learning Trainer in the workplace?

Machine Learning Trainers often encounter the challenge of explaining complex algorithms and abstract mathematical concepts to learners with varying levels of expertise. Adapting course materials to suit different learning styles and staying current with the latest advancements in machine learning require continuous self-development. Trainers may also need to collaborate closely with data scientists, engineers, and curriculum developers to ensure their training aligns with real-world applications. Overcoming these challenges not only enhances teaching effectiveness but also contributes to the overall growth of both trainers and their learners.
What are popular job titles related to Machine Learning Trainer jobs in Oregon? For Machine Learning Trainer jobs in Oregon, the most frequently searched job titles are:
Machine Learning Scientist (L4/L5) - Multi-modal Algorithms for Games

Machine Learning Scientist (L4/L5) - Multi-modal Algorithms for Games

Netflix

Full-time

Medical, Life, Retirement, PTO

Posted 22 days ago


Netflix rating

5.8

Company rating: 5.8 out of 10

Based on 15 frontline employees who took The Breakroom Quiz

57th of 64 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 Team

The Studio Media Algorithms team is at the forefront of algorithmic innovation to enhance and support the creation of Netflix's entertainment content, including games. In this role, you will be embedded within this team while collaborating very closely with a specialized Games Studio R&D team. This incubation-style team is chartered to lead our investments in building new kinds of games leveraging emerging technologies to support our creators and reach player audiences in new ways.

The Role

We are seeking a Machine Learning Scientist to lead the research and development of Large Language Models (LLMs), Vision-Language Models (VLMs), and multi-modal foundations and solutions for games. This role is defined by a mandate for inference efficiency; you will not only build and fine-tune state-of-the-art models but also lead the algorithmic innovation required to make them viable in terms of cost, latency, and quality across a variety of cloud and edge devices.

You will work in close partnership with our Machine Learning Engineers to bridge the gap between "research-grade" models and high-performance deployment, with your focus being on algorithmic optimization-ensuring that our language, visual, and audio models are architecturally optimized for real-time interaction and efficiency.

Responsibilities
  • Model Adaptation & Alignment: Design and own the fine-tuning and alignment of LLMs and VLMs in PyTorch, leveraging modern preference learning and reinforcement learning to enhance reasoning, tool-use, and agentic workflows for interactive game systems.

  • Algorithmic Model Optimization: Lead efforts in model compression-specifically knowledge distillation, structural pruning, and architectural refinement-to create efficient variants of large models that meet strict latency, cost, and quality constraints.

  • Generative Visuals & Diffusion: Develop and optimize Diffusion-based models for Image, Video, and 3D generation, including distillation and efficiency techniques for viable game-time performance.

  • Pragmatic Model Integration: Strategically evaluate and integrate SOTA open-source and commercial models while building internal "layers," adapters, and enhancements to fill gaps in creative control.

  • Multi-modal Interaction: Optimize and integrate audio (ASR/TTS), language, and vision models to enable low-latency, cross-modal reasoning and interaction.

About You (Requirements)
  • Multi-modal Architecture Expertise: Strong foundation in deep learning architectures, with deep expertise in Transformers and Diffusion architectures powering LLMs, VLMs, and generative visuals, including their specific performance bottlenecks.

  • Optimization Specialist: Proven track record in algorithmic model optimization (e.g., distillation, quantization-aware training, or pruning) to reduce FLOPs and memory footprint.

  • Data-Centric Mindset: Skilled in data cleaning, curation, and the creation of synthetic data for complex evaluation and training pipelines.

  • Pragmatic Builder: Ability to prioritize impact by deciding when to use commercial APIs/OSS weights versus when to invest in proprietary R&D to solve efficiency or quality problems.

  • Programming: Expert proficiency in Python and deep learning frameworks (such as PyTorch); ability to collaborate with engineering on low-level performance constraints.

Bonus Experience
  • Prior experience optimizing models for heterogeneous hardware (Mobile, Cloud GPU, and custom edge devices).

  • Expertise in audio-visual multimodal models and video generation.

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.

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.


What Netflix employees say

Pay

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