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Aws Machine Learning Jobs in Oregon (NOW HIRING)

Senior Forward Deployed Engineer- AWS

Portland, OR · On-site

$110K - $152K/yr

... Machine Learning Engineer (Associate - MLA-C01) or AWS Certified Data Engineer (Associate) * 1+ years of experience building reliable, maintainable, and well-documented code * Ability to travel 50 ...

Lead Forward Deployed Engineer - AWS

Portland, OR · On-site

$108K - $143K/yr

... Machine Learning Engineer (Associate - MLA-C01) or AWS Certified Data Engineer (Associate) * 1+ years of experience building reliable, maintainable, and well-documented code * Ability to travel 50 ...

Principal Software Engineer, Pricing Platform

OR · On-site +1

$134K - $180K/yr

... AWS (S3, RDS/Postgres, ElastiCache), Kubernetes/Helm, and Datadog for observability. How you'll ... Partner closely with machine-learning scientists and engineers to create reliable, scalable ...

... machine learning libraries TensorFlow, PyTorch, JAX or Keras Experience with cloud computing platforms like AWS Background in math, statistics, or numerical computation Significant contributions to ...

Senior Data Scientist

OR · On-site +1

$140K - $190K/yr

In this position, you will drive the development of statistical models and machine learning ... Build and optimize data pipelines and analytical workflows using tools like AWS Athena, Redshift ...

... AWS, Azure, or GCP in the context of building and operating AI/ML solutions. * Experience working with data science and machine learning libraries and frameworks such as H2O, TensorFlow, Keras ...

... machine learning solutions that have a direct impact on the business; help design and build ... AWS Cloud Integrations or similar platform • Open-Source products like Kafka, NIFI • ...

Build scalable machine learning and deep learning models using image, video, and multimodal sensor ... Experience with cloud platforms (Azure, AWS, or GCP) and MLOps practices. Ability to handle large ...

Senior Software Engineer, Digital Twin Platform

OR · On-site +1

$122K - $161K/yr

In close collaboration with machine learning engineers, computer vision engineers, product teams ... Experience with distributed systems, data pipelines, and cloud infrastructure such as AWS, GCP, or ...

Deep expertise in building highly available, low-latency machine learning systems, including ... AWS and Google Cloud. Why SentinelOne? AI is redefining how the world operates and rewriting the ...

Applied AI Solutions Architect

OR · On-site +1

$63 - $83/hr

Strong understanding of Applied AI and modern machine learning systems, including predictive ML ... Experience with modern cloud, data, and AI ecosystems such as Snowflake, Databricks, AWS, Azure ...

AI Engineer

Portland, OR · On-site

$50K - $112K/yr

Certifications aligned to data engineering, machine learning, and cloud platforms, including AWS, Google Cloud, Microsoft Azure, Databricks, Snowflake, or related data and AI credentials - Building ...

Data Scientist

OR · On-site +1

Personnel must have experience in cloud-based AI/ML tools, such as AWS SageMaker or Azure Machine Learning, and in implementing models into operational workflows. Preferred Qualifications:

Data Scientist

OR · On-site

Personnel must have experience in cloud-based AI/ML tools, such as AWS SageMaker or Azure Machine Learning, and in implementing models into operational workflows. Preferred Qualifications:

Showing results 41-60

Aws Machine Learning information

See Oregon salary details

$10

$74

$101

How much do aws machine learning jobs pay per hour?

As of Sep 4, 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?

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 does an AWS Machine Learning do?

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 key skills and qualifications needed for an AWS Machine Learning?

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.

Does AWS use machine learning?

AWS offers a wide range of machine learning services and tools, such as Amazon SageMaker, which enable developers and data scientists to build, train, and deploy machine learning models. As a cloud provider, AWS integrates machine learning into its infrastructure to support various applications, making it a key platform for machine learning professionals. Knowledge of AWS services and machine learning concepts is valuable for roles like AWS Machine Learning specialists.

Is AWS Machine Learning a high paying job?

AWS Machine Learning roles are generally well-paid due to the specialized skills required, such as expertise in cloud computing, data science, and machine learning frameworks. Salaries vary based on experience, location, and certifications, but they tend to be higher than average for tech roles with similar responsibilities.

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 cities in Oregon are hiring for Aws Machine Learning jobs?

Cities in Oregon with the most Aws Machine Learning job openings:

Infographic showing various Aws Machine Learning 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 $154,073 per year, or $74.1 per hour.

Senior Forward Deployed Engineer- AWS

Deloitte

Portland, OR • On-site

$110K - $152K/yr

Full-time

Re-posted 17 days ago


Key responsibilities

  • Work side by side with senior client team members to prototype and deliver high-impact GenAI-enabled solutions.

  • Build AI-enabled solutions, agentic platforms, and workflows across enterprise AI platforms, ensuring production-quality code and reusable assets.

  • Embed with clients to identify business needs, translate high-value GenAI use cases into solutions, and lead working sessions to shape solutions and drive client outcomes.


Deloitte rating

8.2

Company rating: 8.2 out of 10

Based on 93 frontline employees who took The Breakroom Quiz

47th of 154 rated financial services


Job description

At Deloitte, Forward Deployed Engineers (FDE) don't just build AI solutions, they help clients turn AI ambition into enterprise-scale impact, pairing leading class engineering with pod-based delivery and vertical expertise. If you thrive at the intersection of product, engineering, problem-solving, and client impact, this role puts you at the forefront of AI transformations.

Work you'll do

As an AWS AI&Data FDE, you will work side by side with senior functional and technical client team members to rapidly prototype and deliver high-impact GenAI-enabled solutions. This requires a highly motivated practitioner who moves with speed and precision, building working software, engaging confidently with senior stakeholders and engineers to bring measurable business impact from day one. Additional responsibilities include:

Client Engagement

  • Embed with clients to identify business needs and translate high-value GenAI use cases into solutions.
  • Partner with leaders, product owners, architects, and engineers to align priorities and delivery.
  • Lead working sessions to shape solutions and drive client outcomes.
  • Prototype and deliver working AI solutions using industry expertise and emerging capabilities.
  • Contribute independently within an FDE pod while mentoring newer team members.

Solution Engineering

  • Build AI-enabled solutions, agentic platforms, and workflows across enterprise AI platforms.
  • Develop scalable AI engineering patterns, tool-use approaches, and human-in-the-loop controls.
  • Apply architecture decisions that balance quality, safety, latency, cost, and model risk.
  • Deliver production-quality code using strong practices in testing, CI/CD, logging, versioning, and documentation.
  • Design extensible functionality, support sprint sizing, and align solutions with senior team members.
  • Contribute reusable assets including code, prompt libraries, runbooks, and reference implementations.


The team

AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by engineering for business advantage, transforming mission-critical operations. We enable clients to stay ahead with the latest advancements by transforming engineering teams and modernizing technology & data platforms. Our delivery models are tailored to meet each client's unique requirements.

Required qualifications 

  • Bachelor's degree (or equivalent) in Computer Science, Data Science or Engineering.
  • 5+ years of experience in software engineering, data engineering, data science, or analytics engineering. 
  • 1+ years of hands-on experience building and deploying GenAI/LLM-powered solutions in client or production environments
  • 1+ years of experience with AWS AI&Data including hands on experience with one of the following key platforms/products: Amazon Bedrock, Bedrock AgentCore, Strands Agents SDK, Knowledge Bases, Guardrails
  • 1+ years of experience with AWS Neptune and OpenSearch
  • 1+ years of experience leading project workstreams/engagements and translating business problems into AI solutions
  • At least 3 of 6 certifications from the following list: AWS Certified Cloud Practitioner, AWS Certified Solutions Architect (Associate), AWS Certified AI Practitioner (AIF-C01), AWS Certified Generative AI Developer (Professional - AIP-C01), AWS Certified Machine Learning Engineer (Associate - MLA-C01) or AWS Certified Data Engineer (Associate)
  • 1+ years of experience building reliable, maintainable, and well-documented code 
  • Ability to travel 50%, on average, based on the work you do and the clients and industries/sectors you serve
  • Limited immigration sponsorship may be available

Preferred qualifications

  • Experience with cloud environments (AWS, Azure, and/or Google Cloud) and common platform services (storage, compute, IAM, networking)
  • Demonstrated ability to work directly alongside client technical teams and program stakeholders in fast-paced, ambiguous delivery environments 
  • Data engineering experience with Spark, Airflow/dbt, streaming, data modeling or ML/data science background feature engineering, experimentation or model evaluation
  • Experience with MLOps/LLMOps practices: evaluation frameworks, model monitoring, and prompt management 
  • Experience with SageMaker fine-tuning (SFT and RFT) for domain SLMs
  • Experience integrating LLM solutions with enterprise systems via APIs, microservices, or event-driven architectures 
  • Experience operating within hybrid onshore/offshore teams 
  • Familiarity with security, privacy, and compliance considerations

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $155,600 to $306,800.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.


Qualifications:

At Deloitte, Forward Deployed Engineers (FDE) don't just build AI solutions, they help clients turn AI ambition into enterprise-scale impact, pairing leading class engineering with pod-based delivery and vertical expertise. If you thrive at the intersection of product, engineering, problem-solving, and client impact, this role puts you at the forefront of AI transformations.

Work you'll do

As an AWS AI&Data FDE, you will work side by side with senior functional and technical client team members to rapidly prototype and deliver high-impact GenAI-enabled solutions. This requires a highly motivated practitioner who moves with speed and precision, building working software, engaging confidently with senior stakeholders and engineers to bring measurable business impact from day one. Additional responsibilities include:

Client Engagement

  • Embed with clients to identify business needs and translate high-value GenAI use cases into solutions.
  • Partner with leaders, product owners, architects, and engineers to align priorities and delivery.
  • Lead working sessions to shape solutions and drive client outcomes.
  • Prototype and deliver working AI solutions using industry expertise and emerging capabilities.
  • Contribute independently within an FDE pod while mentoring newer team members.

Solution Engineering

  • Build AI-enabled solutions, agentic platforms, and workflows across enterprise AI platforms.
  • Develop scalable AI engineering patterns, tool-use approaches, and human-in-the-loop controls.
  • Apply architecture decisions that balance quality, safety, latency, cost, and model risk.
  • Deliver production-quality code using strong practices in testing, CI/CD, logging, versioning, and documentation.
  • Design extensible functionality, support sprint sizing, and align solutions with senior team members.
  • Contribute reusable assets including code, prompt libraries, runbooks, and reference implementations.


The team

AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by engineering for business advantage, transforming mission-critical operations. We enable clients to stay ahead with the latest advancements by transforming engineering teams and modernizing technology & data platforms. Our delivery models are tailored to meet each client's unique requirements.

Required qualifications 

  • Bachelor's degree (or equivalent) in Computer Science, Data Science or Engineering.
  • 5+ years of experience in software engineering, data engineering, data science, or analytics engineering. 
  • 1+ years of hands-on experience building and deploying GenAI/LLM-powered solutions in client or production environments
  • 1+ years of experience with AWS AI&Data including hands on experience with one of the following key platforms/products: Amazon Bedrock, Bedrock AgentCore, Strands Agents SDK, Knowledge Bases, Guardrails
  • 1+ years of experience with AWS Neptune and OpenSearch
  • 1+ years of experience leading project workstreams/engagements and translating business problems into AI solutions
  • At least 3 of 6 certifications from the following list: AWS Certified Cloud Practitioner, AWS Certified Solutions Architect (Associate), AWS Certified AI Practitioner (AIF-C01), AWS Certified Generative AI Developer (Professional - AIP-C01), AWS Certified Machine Learning Engineer (Associate - MLA-C01) or AWS Certified Data Engineer (Associate)
  • 1+ years of experience building reliable, maintainable, and well-documented code 
  • Ability to travel 50%, on average, based on the work you do and the clients and industries/sectors you serve
  • Limited immigration sponsorship may be available

Preferred qualifications

  • Experience with cloud environments (AWS, Azure, and/or Google Cloud) and common platform services (storage, compute, IAM, networking)
  • Demonstrated ability to work directly alongside client technical teams and program stakeholders in fast-paced, ambiguous delivery environments 
  • Data engineering experience with Spark, Airflow/dbt, streaming, data modeling or ML/data science background feature engineering, experimentation or model evaluation
  • Experience with MLOps/LLMOps practices: evaluation frameworks, model monitoring, and prompt management 
  • Experience with SageMaker fine-tuning (SFT and RFT) for domain SLMs
  • Experience integrating LLM solutions with enterprise systems via APIs, microservices, or event-driven architectures 
  • Experience operating within hybrid onshore/offshore teams 
  • Familiarity with security, privacy, and compliance considerations

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $155,600 to $306,800.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.


Education:Bachelor's DegreeEmployment Type:

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