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Machine Learning Trainer Jobs in Oregon (NOW HIRING)

Anno.ai

Senior Machine Learning Engineer

OR · On-site +1

$104K - $143K/yr

Evaluate and integrate emerging MLOps, distributed training, and edge inference technologies to ... software engineering, machine learning engineering, MLOps, or related roles * Experience ...

Bespoke Labs

Machine Learning Engineer

Portland, OR · On-site

* Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection ...

Bespoke Labs

Machine Learning Engineer

Gresham, OR · On-site

* Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection ...

Bespoke Labs

Machine Learning Engineer

Eugene, OR

* Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection ...

Bespoke Labs

Machine Learning Engineer

Portland, OR

* Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection ...

Bespoke Labs

Machine Learning Engineer

Eugene, OR · On-site

* Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection ...

Bespoke Labs

Machine Learning Engineer

Salem, OR · On-site

* Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection ...

Bespoke Labs

Machine Learning Engineer

Gresham, OR

* Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection ...

Bespoke Labs

Machine Learning Engineer

Salem, OR

* Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection ...

OneStudyTeam

Senior Machine Learning Engineer

OR · On-site +1

$140K - $190K/yr

Strong understanding of machine learning fundamentals (model selection, training, evaluation, feature engineering) and statistical modeling. Familiarity with NLP and large language models is ...

Upstart

Staff/Principal Machine Learning Engineer

OR · On-site +1

As a Principal Machine Learning Engineer, you will work at the intersection of applied ML and ... This includes building a unified embeddings platform for training, serving, and managing ...

May Mobility

Lead Machine Learning Engineer

OR · On-site +1

$102K - $134K/yr

We are seeking Machine Learning Leaders in the Autonomous Vehicle domain. As part of our team, you ... Direct experience architecting & training VLA, MMLM, or Generative World Models for commercial ...

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Showing results 21-40

All JobsMachine Learning Trainer JobsMachine Learning Trainer Jobs in Oregon

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 Sep 14, 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?

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 as a machine learning trainer?

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:

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

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

Machine Learning Trainer jobs near you
Infographic showing various Machine Learning Trainer job openings in Oregon as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 25% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $92,327 per year, or $44.4 per hour.

Senior Machine Learning Engineer

OR • On-site, Remote

Anno.ai
Software Development • 51 - 200 employees
Learn more about Anno.aiexternal

$104K - $143K/yr

Full-time

Re-posted 29 days ago

Key responsibilities

  • Design, develop, test, document, deploy, and maintain production machine learning and statistical modeled software.

  • Build and maintain scalable pipelines for training, evaluation, deployment, and lifecycle management of ML models across various environments.

  • Implement automated CI/CD workflows and manage ML runtime infrastructure using containerization and orchestration frameworks.

Job description

Disclaimer: Due to the sensitive nature of our engineering work, Anno.ai enforces strict digital footprint and identity verification. We actively monitor for synthetic profiles, proxy networks, and AI interview assistants; any fraudulent activity will result in immediate disqualification.  

Position Overview 

As a Senior Machine Learning Engineer at Anno.ai, you will design, develop, test, document, deploy, and maintain production machine learning and statistical modeled software to automate processes and streamline our customer's mission operations. MLEs work directly with product, user-facing, hardware, and platform teams to deliver the highest quality products. You will join a team of beasts known as "Annomals" are notable for their practical, mission-driven, and fun demeanor. MLEs work directly with product, user-facing, hardware, and platform teams to deliver the highest quality products, and because of these diverse interfaces, we value good, seasoned judgment in your approach to management, your career growth, and maintaining ethical and responsible practices.  

For this opportunity we are looking for MLEs who have a fairly uniform distribution of talent across a breadth the range of machine learning tasks and skills. You are an experienced MLE, part solid software engineer, and part modeling expert. You have been through the trenches and bring key knowledge and intuition through your combination of training and experience.  

Candidates need to be able to obtain and maintain U.S. Government security clearance (U.S. citizenship required).  Candidates must be able to travel up to 20% of the time. 

What You Will Do 

  • Operationalize machine learning models by building and maintaining robust, scalable pipelines for training, evaluation, deployment, and lifecycle management across cloud, on-prem, and edge compute environments
  • Work closely with autonomy researchers, software engineers, systems teams, and field operators to translate mission requirements into deployable ML capabilities
  • Implement automated CI/CD workflows tailored to ML systems, ensuring repeatable experiments, reliable packaging, and continuous delivery of both up to date models and associated data pipelines
  • Manage ML runtime infrastructure using containerization and orchestration frameworks (e.g., Docker, Kubernetes) and incorporating model serving platforms (e.g., Seldon, KServe, BentoML)
  • Develop monitoring systems to track model health, performance, data drift, system utilization, and mission relevance using tools such as Prometheus, Grafana, and ELK/EFK stacks
  • Ensure ML deployments meet defense, customer, and platform security requirements, with emphasis on data integrity, traceability, and operational reliability
  • Evaluate and integrate emerging MLOps, distributed training, and edge inference technologies to enhance reproducibility, extensibility, scalability, and deployment speed of ML systems 

Required Qualifications 

  • Bachelor's degree in Computer Science, Electrical Engineering, Data Science, or a related technical field (Master's preferred)
  • 5+ years of professional experience in software engineering, machine learning engineering, MLOps, or related roles
  • Experience operationalizing ML systems at production scale, including model training, versioning, packaging, deployment, and monitoring
  • Strong proficiency in Python and familiarity with at least one deep learning framework (e.g., PyTorch, TensorFlow)
  • Hands-on experience with MLOps frameworks and workflow tooling (e.g., MLflow, Kubeflow, Airflow, DVC, BentoML)
  • Experience deploying containerized ML services using Docker and orchestrating workloads using Kubernetes (including air-gapped or constrained deployments)
  • Understanding of CI/CD workflows and DevOps practices applied to ML systems (e.g., Git, Code Review, Metrics Evaluation)
  • Familiarity with monitoring, observability, and logging platforms (e.g., Prometheus, Grafana, ELK/EFK)
  • Ability to obtain and maintain U.S. Government security clearance (U.S. Citizenship required)
  • Ability to travel up to 20% 

Preferred Qualifications 

  • Experience with deploying models and associated runtimes to Edged Devices
  • Experience optimizing models for memory and CPU constrained systems (e.g., embedded systems, microcontrollers)
  • Prior experience supporting U.S. Department of War programs, cUAS systems, or mission-critical autonomous platforms
  • Experience working with diverse or atypical data sources (e.g., Audio/Acoustics, RF signals, EO/IR imagery)
  • Experience deploying and optimizing ML inference on edge or resource-limited compute systems
  • Experience with Explainable/Auditable AI/ML tools and interpretable model design
  • Experience with AI Software Development Tools (e.g., GitHub CoPilot, Claude) 

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