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Machine Learning Engineer Jobs in Portland, OR (NOW HIRING)

Deloitte

AI and Data Science Engineer III

Portland, OR · On-site +1

$121K - $145K/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 ...

Pwc

CTIO AI Engineering Manager

Portland, OR · On-site

$73K - $244K/yr

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

Accenture

Agentic DevOps Engineer

Beaverton, OR · On-site

$70K - $205K/yr

You Are As an Artificial Intelligence and Machine Learning Computational Science professional, you ... Engineer to support our Agentic DevOps initiatives. This role is ideal for a hands-on technical ...

Pwc

NGA AI Engineer Manager

Portland, OR · On-site

$73K - $244K/yr

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

Pwc

NGA AI Engineer Senior Manager

Portland, OR

$91K - $321K/yr

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

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All JobsMachine Learning Engineer JobsMachine Learning Engineer Jobs in Portland, OR

Machine Learning Engineer information

See Portland, OR salary details

$33.4K

$136.6K

$205.2K

How much do machine learning engineer jobs pay per year?

As of Jun 14, 2026, the average yearly pay for machine learning engineer in Portland, OR is $136,560.00, according to ZipRecruiter salary data. Most workers in this role earn between $107,600.00 and $164,400.00 per year, depending on experience, location, and employer.

Is ML full of coding?

Machine Learning Engineers typically do a significant amount of coding, especially in languages like Python or R, to develop algorithms, preprocess data, and build models. Strong programming skills are essential, along with knowledge of frameworks such as TensorFlow or PyTorch, but the role also involves data analysis, model evaluation, and collaboration with teams. Coding is a core component of the job, though some tasks may involve model deployment and optimization that require different skills.

What engineers make $500,000?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data science, and often working in high-paying industries such as finance or technology can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially at large tech companies or startups with significant funding.

What do machine learning engineers do?

Machine learning engineers develop algorithms and models that enable computers to learn from data and make predictions or decisions. They often work with large datasets, use programming languages like Python or Java, and utilize tools such as TensorFlow or PyTorch to build, test, and deploy machine learning systems in production environments.

What are Machine Learning Engineers?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

What are the key skills and qualifications needed to thrive as a Machine Learning Engineer, and why are they important?

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

Which 5 jobs will survive AI?

Machine Learning Engineers are likely to continue to be in demand as they develop, implement, and maintain AI systems, requiring specialized skills in programming, data analysis, and model optimization. Roles that involve complex problem-solving, creativity, and human interaction—such as healthcare professionals, educators, skilled tradespeople, and certain managerial positions—are also expected to persist despite AI advancements. These jobs typically require emotional intelligence, adaptability, and domain expertise that AI cannot easily replicate.

What Does a Machine Learning Engineer Do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

What are some common challenges faced by Machine Learning Engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

What is the difference between Machine Learning Engineer vs Data Scientist?

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

More about Machine Learning Engineer jobs
What are the most commonly searched types of Machine Learning Engineer jobs in Portland, OR? The most popular types of Machine Learning Engineer jobs in Portland, OR are:
What are popular job titles related to Machine Learning Engineer jobs in Portland, OR? For Machine Learning Engineer jobs in Portland, OR, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer jobs in Portland, OR look for? The top searched job categories for Machine Learning Engineer jobs in Portland, OR are:
What cities near Portland, OR are hiring for Machine Learning Engineer jobs? Cities near Portland, OR with the most Machine Learning Engineer job openings:
Machine Learning Engineer jobs near you
AI and Data Science Engineer III

AI and Data Science Engineer III

Deloitte

Portland, OR • On-site, Remote

$121K - $145K/yr

Other

Posted 21 days ago

Deloitte rating

8.1

Company rating: 8.1 out of 10

Based on 86 frontline employees who took The Breakroom Quiz

58th of 138 rated financial services

Job description

AI and Data Science Engineer III

Position Summary

Our Deloitte Human Capital team transforms technology platforms, drives innovation, and helps make a significant impact on our clients' success. We are hiring an AI Engineer to build and operate the data, features, and GenAI foundations that power Human Capital AI products and analytics. You will work with an AI Data Engineer (data ingestion, curation, governance, platform foundations) and a Lead AI Solutions Architect (end-to-end solution architecture, integration patterns, non-functional requirements), partnering closely with product, data science/ML, security, and platform engineering to deliver reliable, secure, and scalable AI solutions.

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 Gemini-class models, and more implemented with strong governance, observability, and cost/performance discipline.

Recruiting for this role ends on 08/30/2026.

Work you'll do

As an AI and Data Science Engineer on the HC Forward team, you will be responsible for building and operating the governed data, feature, and retrieval foundations that support artificial intelligence, machine learning, and generative artificial intelligence solutions.

  • Partner with the Lead AI Solutions Architect and AI Data Engineer to translate Human Capital product requirements into technical designs and delivered solutions, including application programming interfaces, services, pipelines, and containerized or serverless components
  • Build and operationalize large language model-enabled capabilities, including copilots, knowledge assistants, summarization, and policy question-and-answer solutions using secure endpoints, tool calling, and reusable prompt and context patterns
  • Implement retrieval-augmented generation patterns, including document ingestion, chunking, embeddings, vector or hybrid search, and retrieval and evaluation telemetry
  • 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 backfills
  • Implement privacy, access, quality, lineage, monitoring, observability, testing, deployment, and incident response practices for production artificial intelligence and data solutions

A successful candidate would possess these skills:

  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • Ability to lead projects or workstreams
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
  • Strong interpersonal skills and professional demeanor
  • Ability to meet deadlines
  • Ability to provide clear guidance to others

The team

HC Forward is a dedicated innovation partner accelerating the future of Human Capital by building market-aligned products, platforms, and services that apply AI, data, and engineering to modernize HR experiences and outcomes.

Qualifications

Required:

  • Bachelor's degree in Computer Science, Engineering, Statistics, Data Science, or another STEM field
  • 4+ years of experience building and delivering large language model or generative artificial intelligence solutions using Claude-, GPT-, or Gemini-class models, including prompt design, context design, tool calling, evaluation, and production integration
  • 4+ years of experience implementing retrieval-augmented generation, document processing, embeddings, and vector or hybrid search in enterprise environments
  • 4+ years of experience in data engineering, including data modeling, batch or streaming pipelines, structured and unstructured data processing, and feature engineering
  • 4+ years of experience building production inference services and enterprise integrations using application programming interfaces, Representational State Transfer (REST), GraphQL, event-driven patterns, continuous integration and continuous deployment, infrastructure as code, Docker, Kubernetes, and monitoring tools
  • Ability to travel 0-25%, on average, based on the work you do and the clients and industries/sectors you serve.
  • Limited immigration sponsorship may be available.

Preferred:

  • Master's degree or doctorate in Computer Science, Engineering, Statistics, Data Science, or a similar field
  • Cloud or artificial intelligence or machine learning certification
  • 4+ years of experience with Workday, SAP SuccessFactors, Oracle HCM, Salesforce, or human resources data domains
  • 4+ years of experience operationalizing machine learning operations or large language model operations, including evaluation, monitoring, governance workflows, and model or prompt version management
  • 4+ years of experience using Amazon Web Services, Microsoft Azure, or Google Cloud Platform for data platforms and scalable compute
  • 4+ years of experience translating business requirements into acceptance criteria and release increments

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 $113,100 to $208,300.

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.

Deloitte is committed to providing reasonable accommodations for people with disabilities. If you require a reasonable accommodation to participate in the recruiting process, please direct your inquiries to the Global Call Center (GCC) at USTalentCICInbox@deloitte.com.

For more information about Human Capital, visit our landing page at:https://www2.deloitte.com/us/en/pages/careers/articles/join-deloitte-human-capital-consulting-jobs.html

#HCFY26 #IIOFY26

Qualifications:

AI and Data Science Engineer III

Position Summary

Our Deloitte Human Capital team transforms technology platforms, drives innovation, and helps make a significant impact on our clients' success. We are hiring an AI Engineer to build and operate the data, features, and GenAI foundations that power Human Capital AI products and analytics. You will work with an AI Data Engineer (data ingestion, curation, governance, platform foundations) and a Lead AI Solutions Architect (end-to-end solution architecture, integration patterns, non-functional requirements), partnering closely with product, data science/ML, security, and platform engineering to deliver reliable, secure, and scalable AI solutions.

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 Gemini-class models, and more implemented with strong governance, observability, and cost/performance discipline.

Recruiting for this role ends on 08/30/2026.

Work you'll do

As an AI and Data Science Engineer on the HC Forward team, you will be responsible for building and operating the governed data, feature, and retrieval foundations that support artificial intelligence, machine learning, and generative artificial intelligence solutions.

  • Partner with the Lead AI Solutions Architect and AI Data Engineer to translate Human Capital product requirements into technical designs and delivered solutions, including application programming interfaces, services, pipelines, and containerized or serverless components
  • Build and operationalize large language model-enabled capabilities, including copilots, knowledge assistants, summarization, and policy question-and-answer solutions using secure endpoints, tool calling, and reusable prompt and context patterns
  • Implement retrieval-augmented generation patterns, including document ingestion, chunking, embeddings, vector or hybrid search, and retrieval and evaluation telemetry
  • 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 backfills
  • Implement privacy, access, quality, lineage, monitoring, observability, testing, deployment, and incident response practices for production artificial intelligence and data solutions

A successful candidate would possess these skills:

  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • Ability to lead projects or workstreams
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
  • Strong interpersonal skills and professional demeanor
  • Ability to meet deadlines
  • Ability to provide clear guidance to others

The team

HC Forward is a dedicated innovation partner accelerating the future of Human Capital by building market-aligned products, platforms, and services that apply AI, data, and engineering to modernize HR experiences and outcomes.

Qualifications

Required:

  • Bachelor's degree in Computer Science, Engineering, Statistics, Data Science, or another STEM field
  • 4+ years of experience building and delivering large language model or generative artificial intelligence solutions using Claude-, GPT-, or Gemini-class models, including prompt design, context design, tool calling, evaluation, and production integration
  • 4+ years of experience implementing retrieval-augmented generation, document processing, embeddings, and vector or hybrid search in enterprise environments
  • 4+ years of experience in data engineering, including data modeling, batch or streaming pipelines, structured and unstructured data processing, and feature engineering
  • 4+ years of experience building production inference services and enterprise integrations using application programming interfaces, Representational State Transfer (REST), GraphQL, event-driven patterns, continuous integration and continuous deployment, infrastructure as code, Docker, Kubernetes, and monitoring tools
  • Ability to travel 0-25%, on average, based on the work you do and the clients and industries/sectors you serve.
  • Limited immigration sponsorship may be available.

Preferred:

  • Master's degree or doctorate in Computer Science, Engineering, Statistics, Data Science, or a similar field
  • Cloud or artificial intelligence or machine learning certification
  • 4+ years of experience with Workday, SAP SuccessFactors, Oracle HCM, Salesforce, or human resources data domains
  • 4+ years of experience operationalizing machine learning operations or large language model operations, including evaluation, monitoring, governance workflows, and model or prompt version management
  • 4+ years of experience using Amazon Web Services, Microsoft Azure, or Google Cloud Platform for data platforms and scalable compute
  • 4+ years of experience translating business requirements into acceptance criteria and release increments

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 $113,100 to $208,300.

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.

Deloitte is committed to providing reasonable accommodations for people with disabilities. If you require a reasonable accommodation to participate in the recruiting process, please direct your inquiries to the Global Call Center (GCC) at USTalentCICInbox@deloitte.com.

For more information about Human Capital, visit our landing page at:https://www2.deloitte.com/us/en/pages/careers/articles/join-deloitte-human-capital-consulting-jobs.html

#HCFY26 #IIOFY26

Education:Bachelor's DegreeEmployment Type:

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