ZipRecruiter

Log In

1

Aws Machine Learning Jobs in Oregon (NOW HIRING)

Natera

OR · On-site

Build scalable, production-quality machine learning workflows and pipelines using cloud infrastructure (AWS) * Apply modern machine learning techniques including convolutional neural networks (CNNs ...

Tyto Athene, LLC

Machine Learning Engineer

Description Tyto Athene is seeking a driven and adaptable Machine Learning Engineer to help shape ... Proficiency with major cloud platforms, such as AWS, Azure and GCP * Excellent problem-solving ...

Quantiphi, Inc.

OR · On-site

$114K - $137K/yr

As an Elite/Premier Partner for Google Cloud, AWS, NVIDIA, Snowflake, and others, we've been ... We are looking for a Machine Learning Engineer with strong expertise in Google Cloud AI tools, ML ...

iHerb

OR

$134K - $180K/yr

Job Summary: The Machine Learning Engineer will tackle challenging problems and create scalable ... AWS Lambdas and Google functions, etc.) * Exposure to all aspects of the software development life ...

phData

OR · On-site

We are looking for a Machine Learning Architect to join our Machine Learning team. In this role ... g., AWS, Databricks, Cloudera), with familiarity across data and messaging systems such as JMS ...

OneStudyTeam

Senior Machine Learning Engineer

OR · On-site +1

$140K - $190K/yr

You'll use technologies like Python (and Clojure), AWS services (Athena, Bedrock, SageMaker, etc ... Strong understanding of machine learning fundamentals (model selection, training, evaluation ...

Workiva, Inc.

Staff Machine Learning Engineer

OR · On-site +1

As a pivotal member of our Machine Learning (ML) team, you'll spearhead the architecture and ... Experience with Amazon Web Services (AWS) or other cloud service providers * Ability to prioritize ...

phData

OR

We are looking for a Sr. Machine Learning Architect to join our Machine Learning team. In this role ... g., AWS, Databricks, Cloudera), with familiarity across data and messaging systems such as JMS ...

Quantiphi, Inc.

OR · On-site

$66.25 - $80/hr

As an Elite and Premier partner to leading cloud and AI platforms such as NVIDIA, Google Cloud, AWS ... Technical Architect Machine Learning Engineer - Agentic AI & Multi-Agent Systems Experience Level ...

Automation Anywhere, Inc.

OR · On-site

Experience with cloud-based ML platforms (e.g., AWS SageMaker, Azure ML, Google AI Platform) for ... SaaS, Machine Learning, ML, Engineering, NLP, Generative AI, APA, Agentic Process Automation #LI ...

Quantiphi, Inc.

OR · On-site

$122K - $161K/yr

We are an Elite and Premier partner to Google Cloud, AWS, NVIDIA, Snowflake, and other leading ... Senior Machine Learning Engineer Experience Level: 4+ years Work Location: Dallas, TX Employment ...

Netflix

OR · On-site

You will work closely with our machine learning researchers, product managers, and other engineers ... Experience with cloud computing platforms like AWS * Background in math, statistics, or numerical ...

Workiva, Inc.

Senior Applied Machine Learning Scientist

OR · On-site +1

$91K - $124K/yr

Workiva is seeking a Senior Applied Machine Learning Scientist to join our innovative team. In this ... Experience with MLOps practices and cloud platforms (AWS, Azure, GCP) * Proficiency in ...

Autodesk

Senior Machine Learning Test Engineer

OR · On-site +1

$110K - $143K/yr

Job Requisition ID # 26WD98377 Senior Machine Learning Test Engineer Location: United States East ... Experience with cloud providers (e.g., AWS, Azure, Google Cloud Platform) * Experience testing ML ...

next page

Showing results 1-20

All JobsAws Machine Learning JobsAws Machine Learning Jobs in Oregon

Aws Machine Learning information

See Oregon salary details

$10

$74

$101

How much do aws machine learning jobs pay per hour?

As of Jun 11, 2026, the average hourly pay for aws machine learning in Oregon is $74.07, according to ZipRecruiter salary data. Most workers in this role earn between $65.82 and $86.39 per hour, depending on experience, location, and employer.

What is an AWS Machine Learning job?

An AWS Machine Learning job involves designing, building, and deploying machine learning models using Amazon Web Services (AWS) cloud infrastructure. Professionals in this role work with services like Amazon SageMaker, AWS Lambda, and AWS Glue to develop AI-driven applications. They optimize models for scalability, integrate them into cloud-based systems, and ensure efficient data processing. Strong knowledge of machine learning algorithms, AWS architecture, and MLOps best practices is essential for success in this role.

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

To thrive as an AWS Machine Learning professional, you need a strong understanding of machine learning principles, proficiency in programming languages like Python, and experience with AWS cloud services such as SageMaker. AWS Certified Machine Learning certification and familiarity with data pipelines, EC2, and Lambda are commonly required. Strong problem-solving, communication, and teamwork skills help you translate business requirements into technical solutions and collaborate effectively with diverse stakeholders. These skills are essential to efficiently deploy and manage scalable machine learning models that deliver business value in cloud-based environments.

What are some typical responsibilities for someone working in an AWS Machine Learning role?

In an AWS Machine Learning position, you'll typically design, develop, and deploy machine learning models using AWS services like SageMaker, Glue, and Lambda. Daily tasks often include data preprocessing, building and training models, and optimizing performance for production environments. You'll collaborate closely with data engineers, software developers, and business analysts to translate business needs into technical solutions. The role may also involve monitoring deployed models, managing cloud resources, and staying updated on new AWS features to ensure efficient and scalable machine learning workflows.

What are the most commonly searched types of Aws Machine Learning jobs in Oregon? The most popular types of Aws Machine Learning jobs in Oregon are:
What are popular job titles related to Aws Machine Learning jobs in Oregon? For Aws Machine Learning jobs in Oregon, the most frequently searched job titles are:
What job categories do people searching Aws Machine Learning jobs in Oregon look for? The top searched job categories for Aws Machine Learning jobs in Oregon are:
What cities in Oregon are hiring for Aws Machine Learning jobs? Cities in Oregon with the most Aws Machine Learning job openings:
Aws Machine Learning jobs near you
Infographic showing various Aws Machine Learning job openings in Oregon as of June 2026, with employment types broken down into 1% As Needed, 76% Full Time, 21% Part Time, 1% Contract, and 1% Nights. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution, with an average salary of $154,073 per year, or $74.1 per hour.

Machine Learning Scientist, Multimodal AI

Natera

OR • On-site

Other

Posted 13 days ago

Natera rating

7.7

Company rating: 7.7 out of 10

Based on 35 frontline employees who took The Breakroom Quiz

47th of 103 rated laboratories

Job description

POSITION SUMMARY:

Natera is hiring a Machine Learning Scientist to join our AI and computational biology team. This role develops and deploys deep learning models across digital pathology, genomics, transcriptomics, and cell-free DNA (cfDNA) modalities. You will build multimodal AI systems that integrate imaging, molecular, and clinical data, leveraging proprietary genomic and clinical datasets. You will collaborate with scientists, pathologists, bioinformaticians, and software engineers to scale machine learning approaches that advance personalized oncology diagnostics and tumor-informed minimal residual disease (MRD) testing.

PRIMARY RESPONSIBILITIES:

  • Design, implement, and evaluate deep learning models across biomedical data modalities, including histopathology imaging, genomic sequencing, transcriptomics, and cfDNA features
  • Develop multimodal AI architectures that integrate H&E whole-slide imaging data with molecular and clinical data sources
  • Build scalable, production-quality machine learning workflows and pipelines using cloud infrastructure (AWS)
  • Apply modern machine learning techniques including convolutional neural networks (CNNs), vision transformers (ViTs), sequence transformers, representation learning, and foundation model fine-tuning
  • Collaborate across technical and clinical teams to translate machine learning prototypes into validated tools
  • Analyze model outputs to generate reproducible biological and clinical insights
  • Document pipelines thoroughly and communicate data-driven findings clearly to cross-functional stakeholders

QUALIFICATIONS:

  • PhD in Computer Science, Computational Biology, Biomedical Engineering, Bioinformatics, Statistics, or a related quantitative discipline with a focus on machine learning or AI
  • Core experience developing machine learning models for biomedical applications, specifically in medical imaging, computational pathology, genomics, transcriptomics, multi-omics, or molecular diagnostics
  • Hands-on expertise with PyTorch and strong production-level programming skills in Python
  • Practical application of deep learning architectures such as CNNs, transformers, attention mechanisms, and representation learning
  • Experience managing datasets and training workflows within distributed or cloud computing environments (AWS)
  • Proven ability to take ownership of research projects and translate prototypes into robust, deployment-ready workflows
  • Experience adapting pre-trained foundation models for downstream biomedical applications

PREFERRED QUALIFICATIONS:

  • Experience integrating imaging, molecular, and clinical data within unified multimodal machine learning frameworks
  • Technical familiarity with DNA sequencing, RNA sequencing, methylation, and ctDNA assays
  • Hands-on experience with digital pathology software and whole-slide imaging analysis
  • Exposure to survival modeling, longitudinal prediction, or time-to-event modeling
  • Experience applying self-supervised learning, weakly supervised learning, or multiple instance learning (MIL) to clinical data
  • Domain knowledge in oncology, biomarker discovery, or clinical precision medicine
  • Track record of peer-reviewed publications in machine learning or computational biology conferences and journals (e.g., NeurIPS, ICML, CVPR, MICCAI, Nature Biomedical Engineering)

#LI-DNI

What Natera employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

Apply